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            "Installing yfinance and arch and getting the data...\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
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            "[*********************100%***********************]  1 of 1 completed\n"
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 1
        }
      ],
      "source": [
        "print(\"Installing yfinance and arch and getting the data...\")\n",
        "!pip install arch 1>/dev/null\n",
        "!pip install yfinance 1>/dev/null\n",
        "from yfinance import download\n",
        "import pandas as pd\n",
        "import numpy as np ;\n",
        "import matplotlib.pyplot as pl\n",
        "from statsmodels.base.model import GenericLikelihoodModel\n",
        "from datetime import datetime\n",
        "zero,one,two,three,five,ten,hundred=0e0,1e0,2e0,3e0,5e0,1e1,1e2 # some friendly numbers\n",
        "half,GoldenRatio=one/two,(one+np.sqrt(five))/two\n",
        "\n",
        "# get the daily returns of the S&P 500 \n",
        "SPX=download('^GSPC','1928-01-03').dropna()\n",
        "SPX['Return']=SPX['Adj Close'].pct_change()*hundred\n",
        "SPX.index=pd.DatetimeIndex(SPX.index).to_period('D')\n",
        "SPX.dropna(inplace=True)\n",
        "SPX.loc[SPX[\"Volume\"]==0,\"Volume\"]=np.nan\n",
        "SPX"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# get annual series of proportion of year in recession\n",
        "from pandas_datareader.data import DataReader\n",
        "USREC=DataReader(\"USREC\",\"fred\",SPX.index[0].to_timestamp(),SPX.index[-1].to_timestamp()).rename(columns={\"USREC\":\"Recession\"})\n",
        "USREC.index=pd.DatetimeIndex(USREC.index).to_period(\"D\")\n",
        "USREC[\"year\"]=list(map(lambda x:x.year,USREC.index))\n",
        "USREC=USREC.groupby(\"year\").mean()\n",
        "USREC"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        },
        "id": "Jy5MAxAux953",
        "outputId": "e8e31db9-ba4d-4deb-ab6a-91d0070300b7"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      Recession\n",
              "year           \n",
              "1928   0.000000\n",
              "1929   0.333333\n",
              "1930   1.000000\n",
              "1931   1.000000\n",
              "1932   1.000000\n",
              "...         ...\n",
              "2018   0.000000\n",
              "2019   0.000000\n",
              "2020   0.166667\n",
              "2021   0.000000\n",
              "2022   0.000000\n",
              "\n",
              "[95 rows x 1 columns]"
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              "      <td>1.000000</td>\n",
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              "      <td>0.000000</td>\n",
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              "      <th>2022</th>\n",
              "      <td>0.000000</td>\n",
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              "                                                     [key], {});\n",
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              "\n",
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    {
      "cell_type": "code",
      "source": [
        "# fit a GARCH model using arch package\n",
        "print(\"Installing ARCH and fitting model with GED innovations.\")\n",
        "from arch.univariate import ARX, GARCH, GeneralizedError\n",
        "from tqdm.notebook import tqdm\n",
        "results=pd.DataFrame({\"year\":[],\"mu\":[],\"phi\":[],\"C\":[],\"A\":[],\"B\":[],\"kappa\":[]}).set_index(\"year\")\n",
        "results.index=pd.DatetimeIndex(results.index).to_period('Y')\n",
        "\n",
        "for year in tqdm(range(SPX.index[0].year,SPX.index[-1].year+1)):\n",
        "    model = ARX(SPX.loc[SPX.index.year==year,\"Return\"],lags=[1])\n",
        "    model.volatility = GARCH(1, 0, 1)\n",
        "    model.distribution = GeneralizedError()\n",
        "    fit=model.fit(update_freq=0,disp='off')\n",
        "\n",
        "    if not fit.convergence_flag:\n",
        "        mu,phi,C,A,B,nu=tuple(fit.params)\n",
        "        results=results.append(pd.DataFrame({\"year\":[year],\"mu\":[mu],\"phi\":[phi],\"C\":[C],\"A\":[A],\"B\":[B],\"kappa\":[nu/two]}).set_index(\"year\"))\n",
        "\n",
        "results"
      ],
      "metadata": {
        "colab": {
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          "height": 601,
          "referenced_widgets": [
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        "outputId": "68090c89-cbfb-4c35-c12f-b9228d56fa0d"
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      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Installing ARCH and fitting model with GED innovations.\n"
          ]
        },
        {
          "output_type": "display_data",
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              "  0%|          | 0/95 [00:00<?, ?it/s]"
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          "text": [
            "/usr/local/lib/python3.7/dist-packages/arch/univariate/distribution.py:1192: RuntimeWarning: overflow encountered in power\n",
            "  lls -= 0.5 * abs(resids / (sqrt(sigma2) * c)) ** nu\n",
            "/usr/local/lib/python3.7/dist-packages/arch/univariate/distribution.py:1192: RuntimeWarning: overflow encountered in power\n",
            "  lls -= 0.5 * abs(resids / (sqrt(sigma2) * c)) ** nu\n",
            "/usr/local/lib/python3.7/dist-packages/arch/univariate/distribution.py:1192: RuntimeWarning: overflow encountered in power\n",
            "  lls -= 0.5 * abs(resids / (sqrt(sigma2) * c)) ** nu\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            mu       phi         C             A         B     kappa\n",
              "year                                                                \n",
              "1928  0.213503  0.045765  0.128572  1.019873e-01  0.750586  0.674925\n",
              "1929  0.216339 -0.053070  0.174688  2.493820e-01  0.724788  0.569474\n",
              "1930  0.112767 -0.106637  0.126813  2.632717e-01  0.730457  0.836508\n",
              "1931 -0.326928 -0.132279  0.318704  9.778081e-02  0.852799  0.664308\n",
              "1932 -0.126065  0.023032  1.451915  1.129598e-01  0.757731  0.795575\n",
              "...        ...       ...       ...           ...       ...       ...\n",
              "2018  0.070139 -0.025451  0.033166  2.007801e-01  0.799220  0.584140\n",
              "2019  0.134195 -0.054537  0.041216  2.173376e-01  0.717367  0.672854\n",
              "2020  0.251211 -0.217351  0.088885  3.011224e-01  0.698878  0.632700\n",
              "2021  0.131095 -0.022648  0.146024  2.848040e-01  0.520630  0.681681\n",
              "2022 -0.052857  0.104787  0.123903  1.324797e-13  0.931935  1.985266\n",
              "\n",
              "[95 rows x 6 columns]"
            ],
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              "      <td>0.213503</td>\n",
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              "      <td>9.778081e-02</td>\n",
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              "    <tr>\n",
              "      <th>1932</th>\n",
              "      <td>-0.126065</td>\n",
              "      <td>0.023032</td>\n",
              "      <td>1.451915</td>\n",
              "      <td>1.129598e-01</td>\n",
              "      <td>0.757731</td>\n",
              "      <td>0.795575</td>\n",
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              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018</th>\n",
              "      <td>0.070139</td>\n",
              "      <td>-0.025451</td>\n",
              "      <td>0.033166</td>\n",
              "      <td>2.007801e-01</td>\n",
              "      <td>0.799220</td>\n",
              "      <td>0.584140</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019</th>\n",
              "      <td>0.134195</td>\n",
              "      <td>-0.054537</td>\n",
              "      <td>0.041216</td>\n",
              "      <td>2.173376e-01</td>\n",
              "      <td>0.717367</td>\n",
              "      <td>0.672854</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020</th>\n",
              "      <td>0.251211</td>\n",
              "      <td>-0.217351</td>\n",
              "      <td>0.088885</td>\n",
              "      <td>3.011224e-01</td>\n",
              "      <td>0.698878</td>\n",
              "      <td>0.632700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021</th>\n",
              "      <td>0.131095</td>\n",
              "      <td>-0.022648</td>\n",
              "      <td>0.146024</td>\n",
              "      <td>2.848040e-01</td>\n",
              "      <td>0.520630</td>\n",
              "      <td>0.681681</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022</th>\n",
              "      <td>-0.052857</td>\n",
              "      <td>0.104787</td>\n",
              "      <td>0.123903</td>\n",
              "      <td>1.324797e-13</td>\n",
              "      <td>0.931935</td>\n",
              "      <td>1.985266</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>95 rows × 6 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-893cdc7a-2fc1-4cf0-835a-4e65065f07f3')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-893cdc7a-2fc1-4cf0-835a-4e65065f07f3 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-893cdc7a-2fc1-4cf0-835a-4e65065f07f3');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Figure 2.10\n",
        "figure,plot=pl.subplots(figsize=(ten*GoldenRatio,ten))\n",
        "figure.suptitle(\"\\nEstimated Annual Average Daily Returns for S&P 500\",fontsize=22)\n",
        "plot.set_title(\"%s to %s\" % (min(SPX.index),max(SPX.index)),fontsize=18)\n",
        "positive,negative=results[\"mu\"]>zero,results[\"mu\"]<zero\n",
        "plot.bar(results.index[positive],results.loc[positive,\"mu\"],color='blue',label=\"$\\hat\\mu$\")\n",
        "plot.bar(results.index[negative],results.loc[negative,\"mu\"],color='red',label=\"$\\hat\\mu$\")\n",
        "plot.axhline(color='black',lw=1)\n",
        "\n",
        "for year in [y for y in USREC.index if USREC.loc[y,\"Recession\"]]:\n",
        "    plot.axvspan(year-half,year+half,facecolor=\"black\",alpha=0.1)\n",
        "\n",
        "plot.set_ylabel(\"Daily Return (%)\",fontsize=14)\n",
        "plot.axhline(results[\"mu\"].mean(),color='black',lw=1);"
      ],
      "metadata": {
        "id": "9RZs0eXxxj-s",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 663
        },
        "outputId": "4b18b3a7-6e3a-4611-ccb9-ac41c0346071"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1164.98x720 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Figure 2.11\n",
        "figure,plot=pl.subplots(figsize=(ten*GoldenRatio,ten))\n",
        "figure.suptitle(\"\\nEstimated Autocorrelation of Daily Returns for S&P 500\",fontsize=22)\n",
        "plot.set_title(\"%s to %s\" % (min(SPX.index),max(SPX.index)),fontsize=18)\n",
        "plot.plot(results.index,results[\"phi\"],'-',color=\"blue\",label=\"$\\\\hat{\\\\phi}$\")\n",
        "\n",
        "plot.axhline(color='black',lw=1)\n",
        "fisher_error=one/(np.sqrt(252)-three)\n",
        "plot.axhspan(-fisher_error,fisher_error,color='black',alpha=0.2)\n",
        "plot.axhspan(-two*fisher_error,two*fisher_error,color='black',alpha=0.2)\n",
        "#plot.axhline(-two*fisher_error,color='black',linestyle=':',linewidth=1)\n",
        "#plot.axhline(+two*fisher_error,color='black',linestyle=':',linewidth=1)\n",
        "\n",
        "plot.set_ylabel(\"1st. Lag Correlation\",fontsize=14);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 663
        },
        "id": "gVYb5plNuw1X",
        "outputId": "f2b05b0c-23df-48b1-8b48-dc1df032971c"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1164.98x720 with 1 Axes>"
            ],
            "image/png": 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MT28QQrhJvZsAliu+j/jK1Pyb5Bcu+8gvyvvK8dG0UPPJK6LpsYlz6ij5xf6iEELJZqHRfZf7yL9s+EV6efAm9fH9XjML7Ob6Eod5JoTwl4z5h8kvyB4NITxWYNu7o+lLSxzjOWa2u5mdZWZfM7OfRvdfXqme8tdljMw6vXY3Z2z3jLwWaai8RUk54nNlVsjukO9KRReiZrZnmfusp/i6YWd6QR+9X9+Lph9MzX+3/HW+JoSwqor9Ptc/gLwZ+B8lvUjSu0Pvjpcacr7Xye9CCOtLrNPrXI3Etxwk/2/ETWE/bWZvK+Oe3ar00d+vTCGEJSGEV8tvU7pQ/uVL3HT+MEk/knS7mQ1Jbfpl+ZfQ/xlCOFHeg/l4Sb837+PiOdH1QjCzPxQoxn8kzr9nJf1N/jyXSzo9lHnrT/DOBd8XQvhd9Lw2hRAeCSF8Rj09a3/KzDKvDYB2xz3GQGXDNX1W/s/zlOix0czukzex/kUIYUEDytfrnqDg99sVXK6ee7eGJWea2Uj5xcVpJY45Sn5BX66445F7LbuPraTx8uGT4g50FhZZ9yn5fZZli/7hnyS/wLoquSyEsM3Mrpbfp3ieejprarQ4wBR6rk/KyztM/vosV09nK09UeIylIaNn1ciC1LppTxWYX2p5/P4fbImOhAqYWGK5JMnMTpd/YTCuyGqjiiyrRD1eu0I9K6+TNyccVmB5obJknishhM1mtiRab0/1/TBvE6LpLuGzD9+v2+Vf/B1vZgeFEB4zHzImvg//B1XuN9k/wAR5jfEoSd81s3+GXe8Rr/v5XkelPsNS8XNVSpyrIYQ5ZvYNSZ+QB9ZgZo/L76X/dQjhjloKm9AXf7+KCiH8Q9I/4t/NbIa8741z5DWwH5H0zWjZXvJemBfJa+sVQrgw+v/3BXk4PiHxxUncGVvcy3Rash+SbfLP11xJN4UQNtXyvGIhhJvM7AF5s+gT1fP/MdkPwQh5c/q0kdE0/aXLBvnftxEFDjsy8XOpL2yApiMYAxUIISyLOryaKe985hh5k6fjJH3BzN4XQriiyC6q0atmJlWmostTLpGH4sfk/9Tvk98ztE2Sogvu58lrcisR13L+j7w5YzGNHkP4nfLybJGPu5heHtfcnWFmHwqVDW1TayubUhfR1a5bj+1UxgVYoeXx+79Y3qSwmHI6wpoiH1t0N/k5O1v+5cGzIYSdZvZeeXPBSs/TUmp57Sr5HJa1yzrvr16OjKZxb819+n6FEIKZfV/Sf8lrjS+Qt1iZJuneEMJ9RTYvJj2O8Sh5p2evkP8dOSj0jMNa1/O9QqX+BpUToio6V0MInzazH8vHyT5W/n/vfEnnm9mdkl4bQtheyT6LHa7qDesUIBP7e0jSW6MvlE+T3zv+zWjxyfJr6LuSz71AOH5cfovEDhVuNZQ5hngDPC4Pxs99uRBCWGdmq+UBdy8lvhxIiHsEfzI1/8nEdg8V2W5lCKFuHQECjUIwBioUXQDfFT1kZiPkF2dfk/QDM7uuwrDVl+KxEN8SQngkuSB6Hr2GeCpTl7w31q+EEB4tc5u4pmtakXX2KrKskHdF06HyC7hCdpN0tvyCPRb34D2y9+pVl0fy53qAvKYpq9fTafIL3s3qqYmLa3X2r+AYkjTZzIaGELK+gNgntW69xM38loYQzq3D/k6Vvz+/DiF8LmP59DocI6mZr12hsmQO/xLdijA5tW6fMLOJ8tYYkneYF+vr9+tK+X3Lbzezz6inWXW1tcW9RGHhLHmQ2Evei/NXo8X1Pt+TGvU3qCYhhIWSvhM9ZD4M2Wz5CAnnyTuaq0UrfQbT7pQH42Ttf9xbea/r6FQ4vsvMvivv9fvHWbcN9bH4i+F0SL1f0ivltw9kBeMXR9MHMrY7PNrutxVsB7Qk7jEGahRCeDaE8HV5k6ph2jXIxBc5rfIlVNzMMet+pXNUuEan1PO4LZq+qcDyLH+S1w681Mx6hQAze60qb0b9cnknIRskjQghWNZDPRfS6TGN4wuuAzL2fYh6vv1OK/X6xPcbvqPA8jjM/zlR+zBXfj/0FDM7KXuzHsGH4Vgg/7v+tvRyMxssH8ZL8k546unv8l6ZDzezeoSgguepmQ2Vd66WparPW5Nfu7T4XDnbzLKexzvln9POEEKfBYSoufIP5X/j/qVdL4Krfb+qEn3x+HN5U+cvysP6SnmLlXoeZ4Wkr0S/fiJxf20t53vcOqfQOVrsb9Bu6tu+EQoKPizRldGvM+qwv6Z8Bq2Me3/kHUVKu962FH+xfFLWfdfBh977qrwF1iXyZvqfrKGoNTMfHvHl0a/p4ZVujKZvTc1X1O/FWdGvNxTY7qwCfa7E+0tvB7QkgjFQgajDql7hKGpe/Tx5E7XkxWF8kXNgHxSvHHGzvl06ronKX2wsylLP45vy+9M+Z2YfyrroM7ODzeyN8e8hhCflF9cDJf0oqrGO150s6dLiTyVTHHR/nWj2mOV/5CHqxWZ2cGJ+XJv7qagpZVyeqfKLwEIXUaVen/+W3191rJn9W3KBmR0nH7dZkp4bPzRq3h6/Jz8zsxentjMzO8HMRidmx+PEfsXMDkisO1DSN+QXeE9p1/FnaxaV9Svy9/I36bJGZRhiZqcly1VEfJ6eYWaTkvuQd76UWZuqnvdhepHgUUhTXrsM18r/huwt6ZIokMZlOUjSl6Jfq/l8VMXMjpB3UnimvGOgc0IIOxKrVPt+1SLu9fmT8muZK4rcm1qLH8nf99HyjpZqPd9L/a2I/wa93cye+5I1CsU/Uk9I6xNm9gYzOy55HibKc2L0a0339iY04zP4OjO73sxekfEczcxeL28RJu36xcud8nA8XtIt6fc5+kJohXzUBcmH/mr4dYCZnW8ZnfJFfzt+K2/Z8dcQwt9Sq/xMPkzWCWb2odSyr0naV17re1tq2S3yGubpSl1DmNkF8i9ylqh3R5hAa2pUd9c8eLT6Qz3DRtwu/6Nd6PHqxDZrom0ek4/BO0te87lD2cN6dKhnjNo/yv/5XCbptIxyTEttO0dFhipSkWE/VGAYFPmFbTx0woPypnB3R+W/ukhZTlPPsDO/jZ7DZZL2T6xzgrwWJcj/Ef5vtM9b1DMW4zWp/U6WdzIU5B1OXRvtf4O8V86/FHsNUvsaGW0XJL2yjPVviNb9VmLe2ERZl8p7Ob0r2u9d8g56epVH3nPpjuhxh6TLo9fnZYl1To9evyC/kJgVvcfxufOVjDKaPFQH+Zcuf4+2uz1Rzmmp9eMxrrdEZZmtnmFQVkl6USXnUrHzKWO9eOiSIL/f7HpJ18g/I/F7c3KpY8trfO+Plq2LzolfyUPFBvn9pUHSlRlliLd7TN5Z0GWSPplYfqUyhsNp4Gv3ZPp9KuPcPFre+V2Q1zTNjsoTD41ylXqPRTotWvZkucfJeE0eVM/fvfiz25V4Tx+WdETG9lW9X8XOq1Kva7TOHdF6OyTtXenzjvYxJ+t8SK0Tj+W7Rolxias83+NtlkfrXia/vzm5zk3ROs/KP+s3y0PLEvWMN39RapuLsuYXeK4zCyyPz4NzE/O+kyjvHZJ+GZUv/lv/TxUY+7bSz4Ma9BksUZ7XJ97DlfJ7xmdFr/mCxLJZkgaktt1b3noiyFsC/F9U3lvVM77v39UzXNkqSYcXeM0Lvm8VPp8H5f8rHpJ/gXCNvHZ4W+L9mlJg2+MlbYzWuy96LvEQXiuU+H+f2u4geeum+O/u7Gj7EO3v2Ho8Nx48+uLR9ALw4NGsh8obxzgoMX6jvFnQlfJvilfJOzpZIOk3SgTo1HFOkPd+vCb6h7XLP8FCFwpqQDBOLLsrugjYIP8W+MPyWpfMskTbfSD6pxv/4+xVNvkXAf8ZrbdeHgSfjJ7LZ5Q9XvFEeRPNxfKLoYXy2oERpV6D1H7eHa27SKkLmALrx2MaP6PEeLHy5tK/jC4EtsgvfP5DPo5mwfLIv3T4W/S849fn3NQ6h8jD2mJ5yFkp/wb+NSXKeqr8Qm15tN1S+cX3JyUNS61r8o5e/hidc/Fr+kMVGAuz2LlU6nzKWPc4+YXR09Gx18gvxq6RN9cfUc6x5WPJfl3eK/fm6DnPlt+qcK4KB+Np8pqdZfLaml3KrSLjxDbotXtSFQbjaLu95DWECxOv493yv0FZY3BPU+3BOPnYJP9s/C16/q/OOm4t71ex86rU6xqt84lovZsrfc6JfcwpdD4k1hkg/zIrKPUFVhXn+27yliEL1PNFR0itM0xe+7YwWmeJ/Mu2DpUex/iiMp7rzBLnwbmJeYfJawz/rJ6/0c/IQ+C/q8CYydV+HtSAz2CJ8gyTd6R1qfyL2KfUMx72AvkXPK8tsv1w+f3nf4nKuy0692+U31o0IFrv0qicu4xzrPoH43fLA/ET8i/Xtsn/z9wt71V7txLb7y//UmxZ9No/LenHKjEGsfxL7h8nPgdL5f9HX1CP58WDR189LIQgAACAPImGnjlM/sVSuoknAAAV4R5jAACQK2b2Bnko/qe8uTEAADVplZ5yAQAACjKz8fLm2uPkYxdLfv84Td8AADWjKTUAAGh5ZjZNfr/pdnmnZJeEEK5qZpkAAP0HwRgAAAAA0Na4xxgAAAAA0NYIxgAAAACAtkYwBgAAAAC0NYIxAAAAAKCtEYwBAAAAAG2NYAwAAAAAaGsEYwAAAABAWyMYAwAAAADaGsEYAAAAANDWCMYAgF7M7LNmdq2ZLTCzYGZPFlnXzOz9ZvaAmW0yszVmdruZHZ2x7hFmdqmZ3W9mq6PHvWb2QTMbXGD/p5jZ781smZk9a2ZPRPuYVOFzeo2Z/SXax6ro+e2dsd6Lzey7ZnaPmW2Inv+5lRwrsa+XmNnvzGy9ma2LXpfDytjulOi4wcyOKvNYM83sIjMbU01Zy9j/aWb2MzN7PHoNl0TP7eQi27wjcV48Y2aXmdnE1DrDzOx8M7vRzJ6M1l1gZrPN7MCMfVZ8DhUp31Az+7KZLTSzLWY238y+UGo/ZjbAzP4avT83V3LMaPuSr0ti3bqc/wCA4iyE0OwyAABajJkFSask3S/pSEnrQgjTCqz7I0nvlzRH0vWShkt6r6Qpkk4KIcxJrHuNpBMl/UbSXEkDJZ0q6SRJd0o6OST+MZnZ+ZJ+Gq17taRnJb1I0rskPS3phSGEZ8t4Pm+UdJ2khyT9t6TRkv5d0g5JR4UQliTWvUjShZIel7RG0sskvSuEcGWp46SOeXT0miyW9P1o9gWS9pD0shDCwwW2GyHpUUnjJY2U9KIQwn1lHO8iSf8hae8QwpOVlLUcZrZM0jpJN0p6QtI4+ftwgKQvhBD+M7X+RyV9W9LdkmbJz4ePSXpK0ovj983MDpD0T0l/lp8DSyTtI+kDkkbIz4k/JPZb0TlU4jn9RtLpkq6Q9FdJL5V0nqSfhxDOLbLdBZIukb8/t4QQTi3neNG2Zb0u0bp1Of8BAGUIIfDgwYMHDx67PCTtk/j5EUlPFljvMElB0m2KvmyN5o+RtEzSvyQNSMw/RtKwjP38MtrPqan5T8iD0rDU/K9G67++jOcyWB5On5I0MlX2HZJ+mlp/kqQR0c9nRsc5t4rX8O/yILlnYt6e0bw7i2z3/yQtkvSt6NhHlXm8i6L1pzXonHhFxrzh0Xu0VdLYxPwJ8hD3d0kDE/NfF5Xxc4l54yUdlrHvgyRtkXRfan5F51CR5/OaaP1vpebHr/vLCmw3JXoPPxatd3MFr2HZr0u9zn8ePHjw4FHeg6bUAIBeQggLylz1hGj68xDCc7V0IYQ18prF/eRBJp5/Twhhc8Z+/ieaHpKaP0rS6oxt4hrecmrLjpc0WdJlIYQNibI8KK/RfUuy6WwI4ZlQYy2cmU2X1+xdG0JYnNj3YknXSjrRzDoytjtK0ofltdnrKzjelfLaYklamGiGfVFinWlm9ouo6W7cbPhiMxtezjFCCHdlzNso6Wb5lw/7Jxa9Xh6avxdC2JFY/yZJCyS9LTFvZfRepPf9mPxLmUNS8ys9hwo5J5p+JzU//v1tyvYD+XP4rzKPk1T26xKpx/kPACgDwRgAUIuh0XRjxrJ4Xq97jTNMiabPpObfIekgM/uWmR1oZlOjZtEXypui9gprGV4UTf+asexv8vDxgjL2U4lSxzR5E/XnmNkgeTPvO2o5TsEAACAASURBVEMI11V4vJ9IuiH6+aOS3h49ro/2vZe8lvLN8ua7H5U3z/2spNuiY1cr670r9fwPMLORxXZqZgMkPU+9z4lKylHMiyQtDiF0JWdGvy9Rz3NIlulMee3u+5PBtgKVvi71OP8BAGUgGAMAavFoNH1FcqaZmbymVpKmFttBFAQ+KWmtvJY56SPyGtaPSHpMfl/lr+VNt19VZjiZHE0XZyyL5+1Zxn4qUc0xPy6vdf1QpQcLIfxV0j+iX38TQvhl9IjnXSxpoqQ3hBA+GkL4YQjhzZIulXScpHdWekxJMrMZkt4o6U8hhIWJRaWevyXWKeT98mD88zLKUewcKmRygfLFZdzl/TGz0ZK+K+knIYS/lXmMrGPG+886Zvp1qcf5DwAoQy3fEAMAcJv8gv2DZrZEPZ1vfUw9TVoLNtU1s4Hye0P3lnROCGFVapVt8jBwg6Sb5LXQJ8k7SNoh6fwyyhgff0vGss2pdeqlomOa2b7yptBfSQXMmkU1r6dJeiCEcGtq8SXy9+oNki6vcL8T5e/3JknvSS2u6TU3s5fJO6h6SB7qi5Wj1DlUyPAC5YvLmC7fN+QVCp8tc/+FjqkCx816Xepx/gMAykAwBgBULYSw3cxOkdfqfT16SF57+Rl5R0brsraNAtsV8l6BPx9CmJ2x/Hb5/6pjEvcwX2dmKyV92sz+J4TwOzPbTd7TdNLaEMIm9TTpHqrehkXTrKbgRZnZEHnPzEkbovuYKz3mjyUtlNfg1ttEee/Jj6YXhBBWmdlSeS/QZTOzcZL+V167+doQwr9SqySf/6bUsqKvuZkdKekWeXPm1xa4nzhet9Q5NE7SkOS8EMKyxPGz3p+4jM+Vz8xeLg+hb4/uny8oqr1ONxNfFULYqgpel0rO/2LlAQCUh6bUAICahBCeDiGcIGkvefPpQ0IIM9RTA/Z4epvoov8ySe+Q9KUQQlat4LGSXi7p18mOvSLXRtO4ufZbJC1NPd4SLYs7KspqLh3PK9SktpiXZRzzE5Ue08zeIB9+6FJJe5nZ9Kjzrjh0T4nmtcT/7Chs/k4+TNPrszrlUunnHxLrJPd9hDxwr5V0QrLjsox1yzmHrlfv9yhZxkJN6PfUrufE9+W11/8Xvz/ReyRJw6PfJ0S/fyLjmC9LHDPef9Yxk69LJec/AKBG1BgDAOoihPC0vNln7DWSdso7EHpOItC8S9JXQwgXFdhlHB4GZiwblJreIelVqXXiGtJ7o+lL5YEu6Wh5jXa6xrMcD2UcM+7NO3nMyzKOGeSdX0n+hYLkNZ9Z4k61JkrqLlKeQmP3rpD3cH1weoGZjZXfx9urV+gsiVB8kPx+5TsKrHqvfCzrl0rqTC07WtITyR7Co30fEe17vTwUP1WkHOWeQx+XNLZIGd9qZlOTHXCZ2VR5TfhvE+vuJW+RMC9jPydE838gH6f6KvmYzEkPJY5Z7utSyfkPAKgRf1ABAHVnZqdJeq18GKenEvNN3vPyuyRdHEK4sMhuHoumbzWz/xdC2JZYdm40vVeSQgjp2sCku6Nl74n2syEqywxJMyX9LLXvsoQQVqt30I6XdZrZfZLeZGYXhhCWRMecLOlNku5KNOm9WT5ucdqbo3U/LQ/cmU3SE+JANU7Sk4my7DSzmySdY2YnhxBuT2zzGXnrsRtUQhSi/1cesN8YQrityOo3yjuqusDMZsWdRJnZ6+TNtnd5383s8GjfG+ShuOB91pWcQyGEuYWWSZot6a3yobE+npj/79H06sS8dyjVJDtyrfwLjq8pCrrRUGeFhjur5HUp+/wHANTOerfOAQC0OzN7u3pqMj8sDwXfin5/KoTwi8S6l8t7031Qft/ksfLAcb+859y1iXUvlYeQh5R9P+38qIfleP3rJJ0hv2f5l+rpfOh18uFtji2nZ14ze5N8nNuH5KFqlHzIoiDpyGST3Whoo7dHvx4s6Sx5k9wHonm/KFabmdjPyyT9QR56vxfN/rCkSfJ7Rh8qtG20/UXyDrleFEK4r4zjHSOvqfydPNRtlvRICOGR6DndK3/eP5SHuOPkzc3/KOmVIYTtJfZ/n3yIqdmS0p14SdJfkuNfm9nH5e/xnGibPeXvfVf0nOIvKPaSh8txkr4kaX7Gvm+Ix5au9Bwq8ZxuknSqvOOxv8prct8t6ZchhLcX2zbaPki6JYRwajnHi7Yp63WJ1q3L+Q8AKEMIgQcPHjx48NjlIb9oDwUec1Lrvk8ebNbKg/HDkj4nabcK9xskXZlaf4ikT8lD0CZ5b77/kvdUPKLC53SqPExslLRa0nWS9s1Yb2aJMs6s4JgvlfR7eU3oenmT7yPK3Pai6HhHVXC8T8lrK7dF216UWLa3pF9IWi5pa7TexZKGl7nvYq9JkHRuxjbnRu/d5ui4V0jao8LXO0iaVu05VOI5DZP0VXkN+5boNblQ0uAKXpObq/h8lXxd6n3+8+DBgweP4g9qjAEAAAAAba0lergEAAAAAKBZCMYAAAAAgLZGMAYAAAAAtDWCMQAAAACgrfX7cYwnTJgQpk2b1uxiAAAAAACaaO7cud0hhIlZy/p9MJ42bZruu6/k8I8AAAAAgH7MzJ4qtIym1AAAAACAtkYwBgAAAAC0NYIxAAAAAKCtEYwBAAAAAG2NYAwAAAAAaGsEYwAAAABAWyMYAwAAAADaGsEYAAAAANDWCMYAAAAAgLZGMAYAAAAAtDWCMQAAAACgrRGMAQAAAABtjWAMAAAAAGhrBGMAAAAAQFsjGAMAAAAA2hrBGAAAAADQ1gjGAAAAAIC2RjAGAAAAALQ1gjEAAAAAoK0RjAEAAAAAbY1gDAAAAABoawRjAAAAAEBbIxgDAJCwaJF0wgnS3LnNLgkAAOgrBGMAABL++ldpzhzppJOkRx9tdmkAAEBfIBgDAJCwaJFPBwyQTjxR6uxsbnkAAEDjEYwBAEjo6pKGD5f+8Adp2zbpla/0eQAAoP8iGAMAkLBokTRlinTwwdKdd0pr1njN8TPPNLtkAACgUQjGAAAkdHVJU6f6z0ccId16q4flV71KWrWquWUDAACNQTAGACAhrjGOHXOMdOON0hNPSKecIq1f37yyAQCAxiAYAwAQ2b5dWrq0p8Y4duKJ0q9+5UM4ve510saNzSkfAABoDIIxAACRZcukHTt2rTGOnX669ItfSH/8o3TmmdLWrX1fPgAA0BgEYwAAIvFQTeka49jZZ0s/+Yl0223Suef2WbEAAECDEYwBAIjEwzJl1RjHzj9f+tjHpNmzvcdqAACQfwRjAAAipWqMY698pU//8Y/GlgcAAPQNgjEAAJGuLmn4cGnMmOLrzZjh04ceanyZAABA4xGMAQCIxEM1mRVfb/Jkafx4gjEAAP0FwRgAgEhXV+lm1JIH5xkzCMYAAPQXBGMAACJxjXE5ZsyQHnnExz4GAAD5RjAGAEAecJcuLa/GWPJgvHmzNG9eY8sFAAAaj2AMAICkZcukHTsqqzGWaE4NAEB/QDAGAEDlD9UUO/BAadAggjEAAP0BwRgAAHnHW1L5NcZDh3o4JhgDAJB/BGMAAFR5jbFEz9QAAPQXBGMAAOQ1xsOHS2PGlL/NjBnSkiVSd3fjygUAABqPYAwAgHqGajIrfxs64AIAoH8gGAMAIK8xrqQZtUQwBgCgvyAYAwCgnhrjSuyxh9TRQTAGACDvCMYAgLa3fbu0dGnlNcYSHXABANAfEIwBALmwaZP0yCON2feyZdKOHZXXGEsejB97TNq6tf7lAgAAfYNgDADIhf/+b+nII6UNG+q/72qGaorNmCFt2yY9/nh9ywQAAPoOwRgAkAtdXV4ru3RpY/YtVVdjfOihPqU5NQAA+UUwBgDkQjxW8LJl9d93XGNcTTDef39pyBCCMQAAeUYwBgDkQhyMn3mm/vvu6pKGD5fGjq1828GDpYMPJhgDAJBnBGMAQC40MhjHQzWZVbd93DN1CPUtFwAA6BsEYwBALjS6xriajrdiM2ZIK1Y0ppk3AABoPIIxACAXVq70aaPuMa7m/uLYjBk+pTk1AAD5RDAGALS87dul1av953rXGG/f7j1d11pjLFUWjHfulC6+WFqwoPrjAgCA+iAYAwBa3qpVPT/XOxgvWybt2FFbjfG4cb59JcH4rrukz39euuqq6o8LAADqg2AMAGh58f3FQ4fWPxjHQzXVUmMs9XTAVa7LL/fp/Pm1HRcAANSOYAwAaHlxMD7gAK/hrWfvz11dPq2lxljyYPzEE9LmzaXXXbVKuuEG/7mzs7bjAgCA2hGMAQAtLw7GhxziwXP9+vrtO64xrkcw3rFDeuyx0utefbW0ZYt09NEEYwAAWgHBGADQ8uJgfPDBPq1nc+quLmn4cGns2Nr2U24HXCF4M+ojj5TOOMOf25o1tR0bAADUhmAMAGh5jQzG8VBNZrXtZ/p0abfdSgfj++/3dd79bt9G4j5jAACajWAMAGh5K1d6re5ee/nv9RzLuKur9o63JGngQOmFLywdjC+/XBo2TDr77J5gTHNqAACaq6WCsZmdbGZPmFmnmX0mY/n7zexhM3vQzP5sZgc1o5wAgL7V3S1NmCB1dPjvjagxroe4Z+pCnYNt2iTNmiWdeaY0Zoy0zz4+n2AMAEBztUwwNrOBkn4g6RRJB0k6OyP4zgohvDCEcJikb0j6dh8XEwDQBHEwnjBBGjCgfsF4+3Zp6dL61BhLHoxXr+7p0Cvt17+W1q71ZtSS14Lvuac0b159jg8AAKrTMsFY0osldYYQFoQQtkq6RtLpyRVCCOsSv46QVMcBOwAArSoOxgMH+rRewXjZMu9Jup41xlLh5tSXXSbtu690/PE986ZPp8YYAIBma6VgvKekrsTvi6J5uzCzD5nZfHmN8b9l7cjM3mtm95nZfStWrGhIYQEAfScOxpI0aVL97jGOa3brVWN86KE+zQrGnZ3S3XdL5523a0dfBGMAAJqvlYJxWUIIPwgh7Cvp05K+UGCdn4YQjgohHDVx4sS+LSAAoO6Swbijo341xl3R17H1qjEeNUrae+/sYHzFFd4M/J3v3HX+9On+fOo5NjMAAKhMKwXjxZKS39lPieYVco2k1ze0RACAptu6VVq3btca43oF47jGuF7BWOrpgCtp+3bpyiulU07xe4qTGLIJAIDma6VgfK+k/cxsbzMbIuksSb9NrmBm+yV+fa0kuisBgH5u1SqfpoNxoZ6fK9HV5R1gjR1b+75iM2Z4Z1rPPtsz7/bbvZOvuNOtJIZsAgCg+VomGIcQtku6QNIdkv4p6VchhEfN7Mtmdlq02gVm9qiZPSjpY5LeWWB3AIB+orvbp+PH+3TSJB/2aMOG2vcdD9WUvOe3VjNmeGh/5JGeeZdfLu2xh3Tqqb3X33dfnxKMAQBonkHNLkBSCOFWSbem5n0x8fNH+rxQAICmioNx8h5jyTvg2n332vbd1VW/jrdiyZ6pX/ISr92++Wbpox+VBg/uvf7uu3vYJxgDANA8LVNjDABAlnQwnjTJp/W4zziuMa6nadM87Mb3GV91ld9jfN55hbfZbz+CMQAAzUQwBgC0tEYF4+3b/b7fetcYDxjgwzY99JA3qb78cumYY6QDDii8DUM2AQDQXARjAEBLy7rHWKo9GC9bJu3YUf8aY8mbU//jH9I990hPPJHd6VbS9OnS4sXSxo31LwsAACiNYAwAaGnd3d40eehQ/33CBO8sa9my2vbbiKGaYjNm+LjEF14ojRwpvelNxdePe6ZesKD+ZQEAAKURjAEALa27u6cZtSQNGiRNnFh7jXFXl0/r3ZRa6umAa84c6ayzPBwXw5BNAAA0F8EYANDSVq7cNRhLPWMZ16KRNcaHHNIzBFSpZtQSQzYBANBsLTVcEwAAaekaY6k+wbirSxo+XBo7trb9ZBkxQtp/f++I6yUvKb3+mDH+HAnGAAA0B8EYANDSurt79+hcj3F/46Ga4prderv6amm33crf//Tp0rx5jSkLAAAojmAMAGhpWTXGHR1eYxxC9cG2q6sx9xfHjjiisvWnT5f++MfGlAUAABTHPcYAgJa1ebO0YUN2U+pNm3xZteIa41YxfbqH9c2bm10SAADaD8EYANCyVq70aVYwlqq/z3j7dmnp0sbWGFdq+nSvAV+4sNklAQCg/RCMAQAtq7vbp4WCcbVjGS9bJu3Y0Xo1xhIdcAEA0AwEYwBAyypUY9zR4dNqa4wbOVRTtQjGAAA0D8EYANCyStUYVxuMu7p82kpNqceP96GjCMYAAPQ9gjEAoGXFwXj8+F3nT5jgvVH3pxpjyWuNCcYAAPQ9gjEAoGUVCsaDBnk4rvYe464uafhwr6FtJQRjAACag2AMAGhZ3d3S6NHS4MG9l8VjGVcjHqqp2jGQG2X6dOnJJ6WtW5tdEgAA2gvBGADQsrq7e99fHJs0qbZ7jFvp/uLY9OnSzp3SU0+Vv82OHT6mMwAAqB7BGADQshoVjOMa41ZTTc/UH/+49IIXSKtWNaZMAAC0A4IxAKBllQrGy5ZJIVS2z+3bpaVLW7fGWCo/GO/YIc2a5UH/ox9tXLkAAOjvCMYAgJa1cmXhYNzR4U2IN2yobJ/LlnmgbMUa44kTpd13Lz8Y/+Uv0ooV0lFHSVddJd1yS2PLBwBAf0UwBgC0rFI1xlLlzalbdagmyTsDmz5dmjevvPWvv14aMkS67Tbp4IOl971PWru2sWUEAKA/IhgDAFrSxo3+SA/VFKs2GHd1+bQVm1JL5Q/ZFIJ0ww3Sq17lXx787GfeRPzjH298GQEA6G8IxgCAlrRypU9L1RhXOpZxK9cYSx6MFy70e6GLeeAB7736DW/w31/0IumTn5Quv1y6887GlxMAgP6EYAwAaEnd3T4tdo+xVF2N8fDh0tix1ZetkaZP91D89NPF17vhBmnAAOm003rmXXSRdMAB0vnnS+vXN7SYAAD0KwRjAEBLKhWMJ0zwe3Krucd4yhTfthWV2zP1DTdIL3+5d9gVGzZMuuIKD/+f+lTjyggAQH9DMAYAtKRSwXjQIF9WTY1xq95fLEn77efTYsH4X/+SHn20pxl10ktf6kM3/fjH0l13NaaMAAD0NwRjAEBLKhWMpZ6xjCsR1xi3qo4Ob+pdLBjfcINPs4KxJH3lK17z/J73VD6cFQAA7YhgDABoSStXenPnYvcCT5pUWY3x5s3ec/Pzn197+RolHrKpWDC+/nrpyCMLP4/hw71J9ZNPSp/7XEOKCQBAv0IwBgC0pO5uD8WDBhVep6OjsmD8yCPSjh3SoYfWXr5GKhaMFy+W/v536Y1vLL6Pl79cuuAC6Xvfk/70p/qXEQCA/oRgDABoSd3dhccwjlVaYzx3rk+PPLL6cvWF6dOl+fM9xKf95jc+LdSMOumSS6S995bOO8/HhAYAANkIxgCAltTdXfz+YsmD8caN5d9HO3eu10JPm1Zz8Rpq+nRp61avHU67/npp//2lAw8svZ8RI3xc485O6ZvfrH85AQDoLwjGAICWVG4wlsrvgOv++6UjjmjdoZpihYZsWrlSuvvu0s2ok044wZuOx7XlAACgN4IxAKAllROMOzp8Wk5z6q1bpYcfbv1m1FLhYHzTTd68upxm1EmVNjkHAKDdEIwBAC0nhMpqjMsJfY884uE4D8F4zz2loUN7B+MbbvChpo46qrL9VdpJGQAA7YZgDABoORs3Slu21DcY33+/T484oray9YUBA6R99901GG/YIN1xh9cWV9oUPK4xDqG+5QQAoL8gGAMAWk53t09LBeOJEz0klnOP8dy50ujRHjjzYPp0ad68nt9vv92/LKjk/uLYpEk+hvP69fUrHwAA/QnBGADQcsoNxoMG+Trl1BjPnZuPjrdi8ZBNO3f67zfc4MNXHXts5fuqpGYdAIB2RDAGALScOBiXGsdYKq9jqW3bpH/8Ix/NqGPTp0ubNklLl/q90TffLJ1+un8ZUKlKe+8GAKDdVPHvFQCAxiq3xlgqLxg/9pg3Q85Dx1uxZM/UDz8srVtXeW/UMWqMAQAojhpjAEDLqTQYl6oJjcfwzVMw3m8/n3Z2StdfL40cKZ14YnX7qmRYKwAA2hHBGADQcrq7vWfmMWNKr1vOUET33y/tvntPLWweTJ0qDR4sPfGEdOON0mteIw0bVt2+Jkzw15NgDABANoIxAKDldHdL48ZJAweWXnfSJB/eacOGwuvMnSsdfriHw7wYOFDaZx9p9mxp+fLqm1HH+yq3kzIAANpRji4RAADtYuXK8ppRS6Xvn92+XXrooXw1o45Nny4tWiQNGeI1xrUo515sAADaFcEYANByursrD8aF7jN+/HHv3TmvwVjye4tHjaptX+Xciw0AQLsiGAMAWk4lwbhUx1Jxx1t5GqopFgfjN76x9n1RYwwAQGEEYwBAy+nuLm8MY6l0U+q5c6URI6QXvKA+ZetLJ5/sTajrEYzjTspCqH1fAAD0N4xjDABoKSFUVmM8caJkVjwYH354eR15tZrp06VbbqnPviZN8iblGzZ4D92NEIK/FwAA5A01xgDQT23Z4h1P5c369dK2beUH40GDvHY56/7ZHTukBx/MZzPqeitVs14PH/iAdOaZjds/AACNQjAGgH7q1a+WPvGJZpeict3dPi03GEuF75994gkfyimPHW/VW6OD8eOPSz/9qXTffY3ZPwAAjURTagDop/71L2nkyGaXonLVBOP4/tm0uOMtgnHp3rtrdfHF3pR6zZrG7B8AgEaixhgA+qk1a6S1a5tdisqtXOnTetQY33+/tNtu0v7716dsedbIGuPOTunqq72Ts3XrpJ07638MAAAaiWAMAP3Q5s3+yGPtXbVNqbNqQufOlQ47zO9DbnelOimrxcUXS0OGSB/6kNcar1tX/2MAANBIBGMA6IfimuI81hhXG4w3bvQel2M7d0oPPEAz6tigQf6a1jsYL1woXXWV9L73SQcc4PPy+IUMAKC9EYwBoB+Kg0leg/HAgdLo0eVv09Hh02TomzfPgzLBuEehJue1uOQSD92f+pQ0ZozPIxgDAPKGYAwA8trF2bN9eJ/+IA7E69fn7zl1d/vwS5WMh5t1/2zc8RZDNfWodzB++mnpyiul97xHmjxZGjvW5xOMAQB5QzAGAEl33y2dc450113NLkl9JINJ3u737O6urBm1lN3j8ty50rBh0kEH1a9seVfoXuxqff3rPv30p30a1xivXl2/YwAA0BcIxgAgr/mSGjfGa19LBuO8NaeuJRgn37/775dmzKDjraR61hgvXixddpn0rndJU6f6PJpSAwDyimAMAPKLfKlnqKC8y3MwXrmy8mCc7nF5504PxjSj3lVHR+9Oyqr1jW/46/zZz/bMIxgDAPKKYAwg9x56SPrLX2rbx5IlPo17RM67PAfjamqMBw/2+5LjYDx/vjchp+OtXdVrLOOlS6Wf/lR6xzukadN65o8a5V9QEIwBAHlDAzMAufexj0nLl0sPP1z9Pqgxbg0hVBeMpV3vn73/fp8SjHeVDMb77lv9fi69VNq2Tfrc53adP2CAh2OCMQAgbwjGAHJv3rzaw18cjPtLjXHy9chTSFm71nvRrjYYxzWhc+dKQ4bQ8VZaPWqMly+Xfvxj76wuK1yPGZOvcw4AAImm1ABybtMmqavLm83W0vtyfwvGa9Z4zZ2Urxrj+PUfP77ybTs6dg3Ghx7q4Rg9snrvrtS3v+2fu89/Pns5wRgAkEcEYwC5tnBhz89xuK3U9u09QaE/NaXeay//OY/BuJYa4xC8KTXNqHubONGn1dYYd3dL3/++dNZZ0v77Z69DMAYA5BHBGECuzZ/f83NXV3X7eOYZ71134MD+VWO8xx4+jm87BeNnn5UeecSfP8G4t8GD/bWtNhh/5zveq3Wh2mKJYAwAyCeCMYBc6+zs+XnRour2Edc0v+AFXmMcQu3larY1azygjB6dr5BSazCWpFtv9SlDNWWrdizj1aul735XOvNM6eCDC683dqyvCwBAnhCMAeRaZ6e0++7+c7XBOB6q6dBDpS1bvNYx79au9VA8Zky+aozjpuzVBOOODp/eeqvXjB5ySP3K1Z9UG4x/9Stp/fpdxy3OQo0xACCPCMYAcq2z0+913GOP2muMZ8zwaX9oTp2sMc5TMO7u9lAbf9lRibjG+J57pBe+UBo6tL5l6y+qDcaPPy4NHy4ddljx9caM8QC9fXt15QMAoBkIxgByrbNTmj5dmjKltmA8aJB04IH+e9474Nq2zWu98xqMJ0yQzCrfNg7GO3bQjLqY5HjPlYg/a6XemzFjfFpLL/EAAPQ1gjGA3Nq2TXrqKb9Ynzq1+s63Fi+Wnvc8r3WW8l9jHAfhPAfjasQ9Lkt0vFVM3ElZpbcMxMG4lDgY05waAJAnBGMAufXUU147WI8a4z337Bk7N+81xnEgyWvnW9WMYSx5E+x4W4JxYfG92JU0p96xQ1qwgGAMAOi/CMYAcivukToOxmvWSBs2VL6fOBjHNZX9qcY4b51v1VJjLHnoGzTI7zFGtrjJeSXBeNEiaetWgjEAoP8iGAPIrTgY77uvB2OppyOtSixZ4sF4zBi/f7K/1BiPHu2PjRu92Xke1BqMn/9870Rt2LD6lam/qSYYx5+1/fYrvS7BGACQR4OaXQAAqFZnpzRihF/ox8F40SLvpbpcGzZ4J0GTJ0sDB0rjxuW/xjjdlFry51htE+W+snOntGpVbcH4xz+mN+RSqgnG8+b5lBpjAEB/RTAGkFvJXnKnTvV5lXbAFdcw77mnT8eP75/BeM2a1g/Ga9Z4OK61xhjFxZ3MVdIzdWen18JPnlx63bFjfbp6deVlAwCgWWhKDSC35s/vqcGKg22lHXClg/GECf2nKXUyGOfhPuP4C4lagjFKGzzYW0ZU2pR6332lAWVcNYwc6etRYwwAyBOCMYBcSveSO2yYB6p6BOO81xivXevBZOTInmatBGMkdXRUHozLaUYt+bmXt97Q5Zy6KQAAIABJREFUAQAgGAPIpbiX3H337ZlXzZBNWU2p+0ON8ahRPQFFIhhjV5MmlR+Md+7ctXVGOcaMIRgDAPKlpYKxmZ1sZk+YWaeZfSZj+cfM7DEz+4eZ/d7M9mpGOQE0X3Kopli1wXj0aO/ES+qpMQ6hPuVshjVremqK8xiMW/1e6P6gkmC8ZIm0eTPBGADQv7VMMDazgZJ+IOkUSQdJOtvMDkqt9oCko0IIh0q6TtI3+raUAFpFVjCeOrXyzrfioZpi48d7CNi4sfYyNktWMM5DSKHGuO9UEoyzPmulEIwBAHnTMsFY0osldYYQFoQQtkq6RtLpyRVCCH8IIcSXq3+TNKWPywigRcyfLw0dumuonTLFh/upJNQuXrxrT7txKMtzc+o81xgPHdpTe4/GmTRJWr++vM9KPFRTOWMYxwjGAIC8aaVgvKekZF3PomheIe+WdFvWAjN7r5ndZ2b3rVixoo5FBNAqsnrJjccyju8bLsfixbuG6zgY57kDrrVre4LxoEEeNPMQjFeu9NffrNkl6f8qGcu4s1MaMqTn81UOgjEAIG9aKRiXzczeJukoSd/MWh5C+GkI4agQwlETJ07s28IB6BNxME6KL9zLvc94xw5p6dLeTaml/NcYxzXFkv+ch2Dc3U0z6r7S0eHTcoPxPvtIAweWv3+CMQAgb1opGC+WNDXx+5Ro3i7M7ERJn5d0WghhSx+VDUALCSF7+JhKg/Hy5R6O+1uNcbIptZSfoXMIxn2n0hrjSu4vlqSxY6UNG6Rt2yovGwAAzdBKwfheSfuZ2d5mNkTSWZJ+m1zBzA6X9BN5KF7ehDICaAFLl0qbNhUOxuV2wJUeqknKf43xjh3SunW9gzE1xkgqNxgX+hKqlDyNnw0AgNRCwTiEsF3SBZLukPRPSb8KITxqZl82s9Oi1b4paaSka83sQTP7bYHdAejHCvWSO3y4NG5c+TXGS5b4NBmMx471e1zzWmO8bp1Pk8F4zJh8BJTuboZq6it77OHTUsF42TLvoKvaYJyHlgoAAEjSoGYXICmEcKukW1Pzvpj4+cQ+LxSAljN/vk+zLtYrGcs4q8Z40CC/qM9rMI4DcLrGeMGC5pSnXNu3S6tXU2PcV4YM8S+Bli0rvl41QzVJBGMAQP60TI0xAJSrs9MD7POf33tZpcF44MCe2rPYhAn5bUodB5G8db61erU32yUY951yxjKOg3ElQzVJBGMAQP4QjAHkTmenNG2ah+O0SoNxR0fv3nYnTMhvjXEcRPLW+dbyqNcImlL3nY6O0sF43rzCX0IVQzAGAOQNwRhA7hTrDGjqVGnFCmnz5tL7SY9hHBs/Pv81xulgvGWLP1rVnXf69Mgjm1uOdlJujfHee2d/CVUMwRgAkDcEYwC5UqqX3Lhn6sW9BnvrrVAw7m81xnnoIXj2bOmII6T99292SdpHucG40vuLJYIxACB/CMYAcmXlSu95uVQwLqc5dbEa47wG40KdbyWXtZp586R775XOOafZJWkvkyb5Z2nTpuzl1Q7VJEkjR/otCgRjAEBeEIwB5EqpXnLLDcbPPutBsVCN8aZNPkxN3sRBZNSonnlxMG7VkDJ7tg+R9Za3NLsk7aXUWMYrVkjr11cXjM38y5nVq6svHwAAfYlgDCBX4mC8777Zy8sNxlljGMfinpHzeJ/xmjXS7rvv2qFYK9cYhyDNmiUdd1zPe4e+USoYVztUU2zMmNb9MgYAgDSCMYBc6ez02qi9985ePnKkX5CXCsbxPciTJ/deFveMnNdgnGxGLbX2PcYPPCA98QTNqJuho8OnpYJxpUM1xQjGAIA8IRgDyJXOTh86ZujQwutMmSJ1dRXfTxyMi9UY5/E+46xg3Mo1xrNmSYMHS2ec0eyStJ9SNcbz5nnLg732qm7/BGMAQJ4QjAHkSjmdAZUzlnGxYJznGuO1a/MTjHfs8PuLTz6Z8YubYY89fFqsxnivvaQhQ6rbP8EYAJAnBGMAuTJ/fv2C8e67+yMt7zXGcRCOxc+xmpCyZIn0xS9KO3fWXra0P/3J908z6uYYOtTDa7FgXO39xRLBGACQLwRjALmxZo2H1UIdb8WmTvWL/a1bC6+zZEl2bbEkjRvn07wG43SN8cCBHo6rqTH+9a+lr3zF7wOut1mzpBEjpNe9rv77RnkmTZKWLes9PwRvSk0wBgC0C4IxgNyYP9+n5dQYSz09T2cpNIaxJA0a5Bf1eWxKnRWMJZ9XTTBevtynhWoVq7V1q3TdddLrX+/hGM0xaVL2e7tqlZ8vtQbjjRuLf0EFAECrIBgDyI1yh4+Jg3GxDriKBWPJm1PnrcY4hOx7jCVvXl1NMI5DU1atYi3uuMPHuKUZdXN1dGQH41qHapJauzd0AADSCMYAciO+WN9nn+LrlRrLeOdOr03OGqopNn58/mqMN2zw51YoGFfTrDUOTfWuMZ41y1/jV72qvvtFZQrVGNc6VJMkjR3rU5pTAwDygGAMIDc6Oz3Mlmp6WyoYr1ghbd/e/2qM4wCS7nwrntcqTak3bJBuvFF605t8qCY0z6RJfl5s3rzr/FLjhZcj/oJm9erq9wEAQF8hGAPIjfnzS3e8JUmjRvmjUDAuNlRTbPz4/Abjet5j3Iim1DfeKG3aRDPqVhCPZRx/ARKbN6/0eOGlxOchNcYAgDwgGAPIjUqGjyk2ZFM5wXjChPw1pS4WjGu9x7ieNcazZnnP4cccU799ojpxME5/8VHrUE0SwRgAkC8EYwC58Oyz0tKllQXjQp1vxb1VlwrGzz7bu4lpKysnGIdQ/v42bPBehaX61RivWOEdb519tjSA/0BNFwfj9BcfBGMAQLvhsgRALpQ7VFOsVI3xgAE9oSDL+PE+zVOtcVwjXCgYb9vmTZjLFTevHTy4fjXG110n7dhBM+pW0dHh0+T7u3q1n/cEYwBAOyEYA8iFSoePmTLFazm3beu9bPFiD8WDBhXefsIEn+bpPuNSNcZSZc2p47B00EEeknfurK18kjR7tu/v0ENr3xdqt8cePk0G40q/hCpk+HD/jBGMAQB5QDAGkAvxxXo5nW9Jfg9rCN78Oq3UGMZSPmuMi/VKXc2YsnFYOvRQ/4Kh1t6Fn35a+tOfvLbYrLZ9oT6GDfPzJRmM6zFUk+Tv8ZgxBGMAQD4QjAHkQmen1+Jmhb4sxYZsKicY57XGePjw7CGQqqkxjptSx7W7tTanvuYan559dm37QX2lxzIud7zwchCMAQB5QTAGkAuVdgYUB+OsDrj6czDOakYt9QTjSkJKHJZe+EKf1toB16xZ0kteUp/AhfqZNGnX93bePP/87LZb7fseO5ZgDADIB4IxgFyoNhina4w3bfImwaWC8bhxPs1TU+q1a0sH40qbUo8d683S49+r9eij0kMP0elWK8qqMa71/uLYmDG1N8EHAKAvEIwBtLzNm73mt5KL9dGjpREjegfjcoZqkrw58ujR/a/GuNJgvMce2T0XV2r2bO8J/M1vrn4faIyOjsYGY2qMAQB5UKRPVgBoDQsXekdalVysm3lNZzoYL17s01LBWPIOuPJUY7xmjTRxYvayajrfWr7caxPHjvUvCmppSn3ttdIrXtETstE6Jk3yc2fLFn8sX04wBgC0H2qMAbS8SnukjmWNZRwH48mTS28/YUL/qTEeOdJrbCutMZ40yb9kSDe3rcS2bX7f6ktfWt32aKx4PO/ly+s3VFOMYAwAyAuCMYCWV+kYxrEpU3p3vtXfa4wLBWMzadSoyjvfikNTuoOmSixb5jX+8X3faC3xe/zMM/Ubqik2ZozfCrF5c332BwBAoxCMAbS8zk6/RzYeW7hcU6b4OMbbt/fMW7zY7z0eNar09nmqMQ6heOdbkr+G5dYYb93qIXqPPfz3/8/encdJVpYH3//dta+97z07M8wCIiIhEh9ElBGiRjRiFNfHN+prXJJoNNFoDCZGg6BGoyb6xjyPn8do5AFUNAioIEhQARFhZIZZYPbpvWvtqq7tfv84fXqZ7uo6VXWqa+nr+/n0Z3q6lr67u/r0uc513ddVTcbYzNpLYNyYzMB4ZGQhMC63OqOYSkr4hRBCiHqQwFgI0fDMZkBKlfe4DRugUFia6Tx92sgWW3muZgqMUymjZHm1wLijw3qAYs4wNoOmgYHKM8YSGDe2szPGg4PGxSM7mK9HKacWQgjR6CQwFkI0vEq75JpjhhbvM7Yyw9jU3Q2JhNGQqNGZgYfZfXol5WSMzezw4lLqsTHjQkO5JDBubIsD40OH7NtfDBIYCyGEaB4SGAshGlo2C8eOVVbaudIs43IC454e499m2GdsBh52lVKbgbFZSj0wAPk8TE2Vv7aTJ8HvN7pbi8bj9xtbC8yMsZ2Bsfkzl8BYCCFEo2v5cU3JZJI777yz3ssQQlTo9Gk/udzlpFJPcOedp8p6bDzuBl7Mj360n1DoGFrDyZMvYXb2KHfeebDk448f7weew/e+9wBbtyYq+wLWyJNPdgDP4/DhR7jzzpXrv5PJZ3HmTCd33nl/yef7yU+GgWdx4MB9RKMpzpwZAC7kllseYMuW8r4XjzzybLq62rjrrp+V9TixdsLhy/jFL5KcOdNHoXCQO+982pbnPX48CFzGvfc+htZVzPsSQgghaqzlA+N8Pk9vscGeQoiGd/iw0SVrzx5P2b/LPT3g9RZIJrvo7Z1hetpFLudg82aXpefatCkAgMPRS2+vv/zFryGXy/g+bdgQpLd35Q3U3d1uUilr38dMxkj17djRht8fYssW4+vXuq/s70UkEmZwUI7Fjay3t8BTT3UBsGuXtd8PK5Ryzf3bSW9v3pbnFEIIIWpBSqmFEA3t2DEvABs2lL/R15i/m2FszA0w/29vb9bS4zs6jHbWkUjjX0OMx50AhELFg49wOE8y6UTr0s83NeXG78/j9xubint6jO/Z5KS77LWNjbnp67P2PRf10dWVIxo1XucbN9o3W8l8PSYSTtueUwghhKgFCYyFEA3t4MEAHR3Z+cCsXP39GUZHPQCMjxtBndUgrZkCYzPwWC0wDoXy5POKVKr0oX962kVX18KcK/P9ycnyvhf5PIyPe+jvz5T1OLG2ursXficquQhVjNercbsLxOON/zskhBBifZPAWAjR0A4cCLBr10zZo5pMfX3Z+Uzx+LgRIPf2WgvS2tuNILMZAmMz8AiHVw+MjfuWzt5NTrrp6loIlsLhPG53gamp8jLG09Mu8nklGeMGZwbGXV1ZQqEKWo8XoZTx2rHymhOiEo8+GuIf/mFTvZchhGgBEhgLIRrW7KziyBE/u3fPVPwcfX0Zxsc95PNGSa9S2nL22e3WBIP5+RLTRhaPO/F4Cni9xeukyylrnZpamjFWysgal1tKbWbr+/okY9zIzJ+1ndliUygkgbGonQceaOc73+lldrbCq6dCCDFHAmMhRMM6fNhPPq/YtavywLi/P0M+r5iacjM+7qarK4erjDi3oyPXFBnjRMK5arYYyg2Ml2aMwcgqTk2V970YGzMCYymlbmzmz3rjRvsD43A4L3uMRc0kk8ZrS15jQohqSWAshGhYBw4YXaGrCYzNEt7RUTdjY56yM5ft7bmmyRivtr8YFsqsS51A5vNG+fjijDEYgXH5GePy9nWL+ujuNn7WdjbeMoXDOckYi5pJJo1TWQmMhRDVksBYCNGwDhwI0NaWY2io8myjmakcG/MwPu4uu4lXM2WMSwXGVjPG0aiLQkEtyxhXUko9NubB7S7MNzITjWnjxjR+f54LLkja/tzGHuPG/x0Szck8nsnFFyFEteQvlRCiYe3fX13jLVgcGBsZ43JP/Nvbcxw75qt8AWskHncSDq8efFptvmWWSy/uVGz+PxJxkc+D0+I5qDmqySGXYRtaR0ee++57rCY/J2m+JWpJSqmFEHaRUxUhREPKZhWHD/urKqMGo7O0x1Pg5Ekv0ajLckdqU7NkjONxl217jM3O052dSwPtrq4s+bwqq7S8kvJ1UR+1unhhBsZW5mcLUS4JjIUQdrF8dqOUei3wYqCPswJqrfUrbF6XEGKdO3LERy7nqDowVsroiPzb3waB8ve6trfnSCadZLMKt7txz+ytlFL7fAWcTj1/IllMsYyxWYZ+dsfq1YyOejj/fPvLc0XzCIdzZLMOZmcVPl/j/g6J5iSBsRDCLpauDyulbgS+AWwBIsDkWW9CCGErs/FWNaOaTH192fnnKzd7ae6NjUYb+6TLSldqpYyscakTSHMf8dnBr/n/iQlr+4y1NkupJWO8npXTDV2IcpmvK3l9CSGqZTVj/GbgOq31LbVcjBBCmPbvDxIK5WyZq9rfn+HRR8MA9PaW33wLjC7NPT2N2UBqdlYxO+somTEGazNlp6bcuFyFZYG2mUE2S61LiURcZLMOGdW0zpmvo3i8cX+HRHPSeiEgLlUJI4QQpVjdUeQAHqvlQoQQYrEDBwLs3JmqqvGWaXFgVm4p9eLAuFGZJ4alMsZgLWNslkqf/b1fCIytfS9kVJOAxYGxBC7CXrOzinzeOFBJxlgIUS2rgfFXgTfWciFCCGHK5eDQIT+7d9uzN9UMzLzegqWs6mLt7cb9G3mWsRlwlOpKDVYDY/eyUU0AwWABj6dgeWTT2JgHKL98XbQWCYxFrSzOEsvrSwhRLatneh3A65VSe4HHgSVnTFrrP7V7YUKI9evpp/1kMtU33jKZgVlfX6bsDHQzZYytBP3hcI6TJ72r3qdYcy2ljKyx9cDYuF9/v2SM1zPzgo0ELsJuiwNjyRgLIapl9UxvDwul1LvOuk1aTAohbGU2yrIrMDYDs3L3F4PRlRoaO2Nsfym1m3POSa14W1dXznJgPDrqwenUK2afxfphvi4lcBF2k8BYCGEnS2d6Wusrar0QIYQw7d8fIBDIs2lT9Y23YGGPcSUlvR6PJhDIN3TGOB431mY1MDbvvxKtVx/H1N2d5cwZj6V1jY156OnJ4pTz1XXNrGSIxRr3d0g0JzMYDgRKX/ATQohSrO4xBkAp5VNKna+UOk8p5avVooQQ69tTTwXYuXMGR1lHqOI6OnKEwzk2bqws0O7oyDV0xtgsUbXalXpmxkGhsPLtiYSTbNZRNMvb3Z213JV6bMwtHakFXq/G6y1IKbWwXTJp/JHo789IYCyEqJrVOcbuuVnG08BvgCeAaaXUp5VS1s6QhBDCglzOCIztKqMGcDjg//yf/bz5zaMVPb69PdfgGePySqm1VszMrHz4n5w0vs7u7pUzxl1dOaanXeQt9DAbHfVI4y0BWCvhF6Jc5mtKAmMhhB2s5mNuwOhK/U7gXGAH8CfAm4BP1WZpQoj16OhRH7Oz9jXeMm3YkMHvL5ImLaGjo7ED40TCidOp8flKf31mVrnYSeT0tHGts7OzeMa4UFAlvx9aGxljGdUkwGjAJRljYTdzj/HAgBEYa+l6I4SogtXA+PXAH2utv661PjL39r+BtwFvqNnqhBDrjtl4a/duewPjarS354hGG/ekPpFwEg4vnzu8EjMwLrbPuHTGODt3v9WLheJxJ+m0UzLGAjCqGVbb2y5EJczAuL8/Sy7nYHbWhsH3Qoh1y2pg3A4cWeHjRzBGOQkhmkQi4eDFL34299/fXu+lrOjAgQA+X57Nm9P1Xsq8Rs8Yx+NOS2XUUDpjbO4fLrbHuKcnO3e/1b8fMqpJLGYExo17cUk0p2TSicdTmK9wkXJqIUQ1rAbGvwFWmlX8ZyyMcRJCNIGnn/YTjbrYty9Y76Ws6MCBAOeem2qoTsbt7XkSCRe5lZOodRePuyw13gIrpdQulNLzY6rOZnarnphYPWM8Omp0rpaMsQDZYyxqI5FwEgzmSx7XhBDCCqspkL8E7lBKXQn8Yu5jzwOGgN+vxcKEELVx/LgXwPLInbWUzxuNt17xisl6L2WJjo6FWcbFSozrqZyMcamZspOTbjo6criK/HXo7jYzxqsHxmNjxutLulILkIyxqI1k0iGBsRDCNlbnGN+vlDoXeDewa+7D/xf4stb6dK0WJ4Sw3/HjxqS1kZHGC4xPnPCSSjltb7xVLTMwjkSqD4wzGcX1128hk1EMDGSWvXV15coeU5VIOOdLnEspXUpdfIYxQCBQwOstWCqlVkpbXpdobWbzLa2xtBdeCCuSSSfBYEECYyGELSxvmpsLgD9Sw7UIIUq4994OHnkkzAc/eKLi52jkjPH+/UZ59+7dyTqvZCmzrNiOWcY339zL3Xd3sWVLiocfbptvHmPyeAr092fYsiXN3//9M4RCpTtNG823yiulLpa9m5pyz2eFV6KUkTUu1XxrdNRDd3e2aOZZrC/hcH6+OZLPJ62DhT2MwFgyxkIIexQ9ZVFKXQQ8prUuzL1flNb6UdtXJoRYYmLCxd/93WbicRfvfvcpAoHKRg+ZGePxcQ+5HA0VuOzfH8DrLbBlS+M03oKlGeNqTE+7+Ld/G+T3fi/KF75wGK2NE7kzZzyMjBhvZ854eOYZHz/7WQe/+lWYyy+Plnxeo5TaWibb69W43YVVM8bnnbd6xt5KYCyjmsRi5oWbWMyFzyevC2GPRMLJwECmZLd9IYSwYrUjyCPAADA2974GViqA0oBcohOixj772Y3zf/SPHfNVNM5IayNjHAzmSSadTEy4GRhonJPUAwcC7Ngx01DBOtiXMf7KVwZJpZy8730nASP7Gg7nCYdTnHtuav5+6bTiBS94Dvv3B0oGxrkcpFJOy823YPVGSFNT7qIdqU1dXTlOnvSuep+xMU9DdRYX9WUGxvG4Uy6YCNtIxlgIYafVdrJtBcYXvb9t7t+z37bVcoFCtApzf10lHnywjbvv7uIlL5kC4OhRX0XPMz7uJp12cvHFcQDOnFk9uFlLhYLReKvR9hfDQmBcTcb4yBEft93Wy6tfPc7WrasHjD6fZtu2FE8+WbpzuHkiWE5gHA6vHBin04qZGeeqpdRgZIxL7TEeHfVIACTmmRUN0oBL2CmRMC4KBgIFHA4tgbEQoipFA2Ot9TGt50/jNXB87mNL3uZuE0KsIpeDP/iD8/nbv91SdnCcSjn4x3/cxJYtKT760WM4nZpnnqksMDb3F19ySQxorH3GJ096SSYbr/EWGIGq358nGq38pOuf/mkDwWCed7zDWr/C3btn2L8/UPL1YlYRWN1jDMUzxman6c7O1cuyu7uzRCLFx1clEg6SSaeMahLzJKMn7Kb1QldqhwOCQRkJJoSojtXep88AvWd/UCnVPXebEGIVkYiLRMLFHXd087WvDZT12K9+dZDTp7185CPHCQQKDA/PVhEYG4/73d9tvMB4//4AQEUl4muhvT1Xccb4v/+7jZ//vJ23ve0MHR3WAtg9e2aYnnYzOrr6Xl7zRNCewNj4+kpljLu6cmitin4/xsdlVJNYaqGUusH2SYimlckocjkHwaDRb0NmZQshqmU1MFasnBkOAbKJTIgSzEZFGzak+dd/HeauuzotPe6pp/x885v9vPKV4zznOQkAtm5Nc+xY5Rljr7fApk2zdHZmG2pk04EDAdzuAtu2NeYhpaOjssA4lzOyxZs2pfmjPxov/YA5ZmfuUuXUZmlqOYFxscyK+TpdbVwTLATOxRpwmcG8lFIL0+I9xkLYwezob1YjSGAshKjWqmd5SqkvzL2rgU8ppRancpzAJcBjNVqbEC1jetr4VfvIR47z1a8O8vGPb2FwMMMFFxQfS5TPwz/8w2ba23O8972n5j++dWuK//7vtoo6Sh8/7mPDhlkcDhgczDRUxthovJXC7W7M3Rnt7fmKmm/ddlsvzzzj56abDpf1te3YkcLp1OzfH+BFL4oUvZ8ZaNixx9gspS7dfGtxYJxadvvYmPG6klJqYSo1JkyIcpnHsGBQAmMhhD1KZYyfNfemgN2L/v8sYDvwKPA/a7g+IVqCGXD092e48cYj9PVl+Iu/OIdTp4oHprfc0suTTwZ5//tP0N6+EPRs2ZIml3Nw6lT5jbOOH/eyaZORkR0YyDRM8y2tjcB4587GLKOGyjLGsZiTr3xliIsvjlkau7SY16vZvr10A66FjLG1cU1QupS61B7jnp7skvufbWzMeL339krGWBg8Ho3XW3xMmBDlMjPGiwNjufAihKjGqoGx1voKrfUVwNeB3zf/P/d2ldb6/9VaH1qbpQrRvMwAoqsrS0dHnn/6p8Pkcor3vW87icTyX8OxMTdf/vIwz3telKuuml5ymznjt9x9xrmc0eBq06ZZwAiMR0Y8FXfKttOpUx7icVfD7i8GY49xuRnjf/u3QWIxYzyTWmnYXQl79iRLNuCqpCt1KJRnZsa5rHnW1JSbUCiH17v6i8IstS5eSu2hszNb8nnE+tLWlpPARdgmmTT+di4OjM1gWQghKmFpj7HW+q1a61itFyNEq5qacuPxFOabhGzZMsuNNx7h2DEfH/rQtmUByo03biSXU3zoQ8eXBVRmYFzuyKaREQ+5nGM+Yzw4mGF21lHVCCK7HDjQ2I23wMgYx2LFOzGf7fhxLzff3Ms110ywc+fycmMrdu+eIRZzrVpZkEg4cTg0gUDB8vOaQfTZJ5FTU66S+4sBAoECfn++aGA8NiajmsRy4XCeWKz+xxvRGs6+KCil1EKIalltvoVS6gql1FeVUncqpe5Z/FbLBQrRCqanXXR25pYEuRdfnOCv//oYv/hFOzfeuGk+K/jTn7Zz772dvP3tp9mwYfkezVCoQG9vpuzA2OxIvXmzGRgbmeNG2Gd84EAAl6vAOedUFkCuhY4OI2C0emL/+c9vwOPRvPOd1sYzrWTPHmMP+v79xcup43EXoZAxrsSqYqNzpqbcJfcXm7q6cquWUsv+YnE2CVyEnYo132qEKighRHOydCqllPqfwA+BMPBCYBzoBC4CnqzR2oRoGZOT7hVH4FxzzSRvecsIt97ay7e+1Ucy6eDGGzexffsMb3zjaNHn27o1zTPP+MtagznDeOPGhVJqaIzAeP/j66+SAAAgAElEQVT+IOeck8bjadwzmvZ2IzC2Uk79yCMh7ruvg7e+dYSeHut7f892zjlp3O4CTz4ZKHqfeNxZVhk1LHQIXh4YW8sYg9GZerWMsYxqEmcLh9d2D+j4uJvx8dXHnYnmtbDHeGFcUz6vSKfLuEoohBCLWD16fAB4j9b6OiALfFhr/RzgG0CiVosTolWYGeOVvPvdp7jiimk+97kNvP/92xkbc/ORjxxfteP05s1pjh71lXVl/PhxH8Fgfj7wGRxsjMDYbLy1a1fjllHDQsa4VOl5Pg+f/exGBgdnef3ri1/csMLt1uzYkZovNV9JJYFxsQ7BU1MrX8BZSbHAOJ1WRKMuKaUWy4TDa7fHuFCAd71rBx/72JY1+Xxi7a3UlXrxx4UQolxWA+NtwI/n3p/FmF8M8EWkK7UQJa1WoupwwN///TPs3j3Dr34V5tprx3nWs4qPcQIjY5xMOpmYsJ4NOX7cy+bN6fly7ra2PIFAvu6zjEdGPESjrvm5vY1qIWO8+knX97/fzcGDAd773lO2NJ8yG3AVimwhTiScZc0whpVPIHM5IxtuNWNcrJTaHNUkGWNxNiNjvDZ7jB98sI1nnvGXveVENI9k0onbXZivNJLAWAhRLauB8SRGGTXAKeD8ufe7gfLqOYVYZ7Q2SlRXG4Hj82k++9nDvPOdp3j3u08VvZ+pks7Ux4/75suoAZRqjJFN+/cb2dBWyBj/7GfGfvELL4yzd+900fuVY/fuGRIJFydPrvxzMgLj8sq1VzqBnJ42LrJ0dlrPGEci7mXNyMxRTRIYi7Ot5R7Qb3yjH4DxcQ+zsxW0hBcNL5l0zGeLQWZlC1FvqZSDmRlHU+/ztxoY/wx4ydz7NwNfUEr9L+BbwI9qsTAhWkUy6SCbdZRsatTTk+NtbxshFCrdXXjr1vI6U2cyijNnPPMdqU2Dg5m6l1IfOBDA6TRm9jayUoHxD37QxQc+cA7nnJPixhufrmg800r27DEuGBTbZxyP25Mxnpw0vq7ubqsZY+P1bAbUptFR4/UkpdTibOGwsQc0lartHtADB/w88kgb555r/O7UuypG1EYy6ZzfXwySMRai3r797V5e8ILnNPU+f6srfw9GEAzwKeBGjGzxzcDbarAuIVrG1JQROFgtUbWipydLMJi3nDE+edKL1mq+I7VpYCAzH8jUy4EDAbZtS+HzNfYlRp9P4/UWVmy+9c1v9nH99Vu56KI4//IvB1etDijX1q0pvN5C0c7UZlfqcqx0ArnwOrWaMTZnGS/9fpil1NKVWpzNvIBT64zef/xHP4FAnj/5E6Mj/OnT9a2KEbWRSCztr1CsqaAQYm1Eoy683gJ+v/XxkY3G6hzjKa316bn3C1rrG7TWr9Baf0BrHbFrMUqpq5VSTymlDiulPrTC7S9QSj2qlMoppa616/MKUUvmPkyrAYcVShnl1FYzxmd3pDYNDs4SjbqYmanN1b1CAWZnFbkcK5bWaG2UUjd6GbWpoyO3JGOsNXz5y0N89rMbueKKaT7/+cNLMhh2cLlg586Z+ZLzxfJ5I2tSbmDsdhtB/tLA2MwYWy+lBpY14Bobc9Penmv4Cx1i7Zkl/6UC41zO2KufTpdfdjE25ubuu7u45pqJ+YzxanPARfMyMsbLS6klMBaiPiIR13x1XbMqullOKdVl9Um01lPVLkQp5QS+BOwFTgIPK6Vu11ovHgd1HKPZ1weq/XxCrJVaZIzByCT+8pdtlu5rzjDetGlpYLx4ZNM556SXPa5ab3vbTh5/PDT/f6dT43IZb06n8TY97W6awLi9fSEwzufhhhs2cdttvbzqVeN86EPHcdbofGz37hm+//1u8nmWfA5zXEm5pdSwfKas+Tq1mu02L/ScHRiPjnokWyxWtJAxXr0B1113dfHxj2/hwIEAH/zgibI+x80396I1vO51Y/T2ZnG7C5IxblGJhHNJLwMJjIWor5YOjIEJoNQlfzV3HzuOQpcAh7XWTwMopf4TuIZFc5K11kfnbmveHL1Yd2qRMQYjY/yDH/SQSDhK7ks+ftxLV1d2WQC1eGST3YGx1sa+2Oc+N87v/E6MfF6Ryxlv5vv5vMLh0LY1qqq1jo4c0aiLTEbxN3+zlZ/8pJO3vvUM73rXadv2FK9k9+4k3/52H8eP++b3l8PCCaA9gbFRAhUIWDu8mqXUZ3emHhtzy/5isSKrpdS33NILGEHu1VdPlezSb5qZcXDrrb1ccUWE4WHj2DY4mOH0ackYt6Kzq2X8/gJOp5bAWIg6mZ5u7cD4ijVbhWEYWHxp+CTwu5U8kVLqHcA7APr6+qpfmRBVMDNxdh8szM7UR4/6OP/81TOuZ3ekNpmBcS2a00SjTnI5By98YYTrrhuz/fnroaMjx+OPB/nzP9/OQw+18ed/foI3vrH2X9viBlyLA2MzwCi3K7X5mKXNt4wZxlYDfL+/QCCQX6GU2sPu3c1RASDWlpXA+MABP088EeKd7zzFd77Tyyc+sZlvfGM/bnfp0vzvf7+beNzFG9+4MD98aGhWMsYt6uyu1EoZM42lK7UQ9RGJuBgebu6//0UDY631fWu5EDtprb8KfBXg3HPPlY1uoq6mp120t+dw2Ty+c3Fn6tKBsZdLL40t+3hPTxaXq1CTkU3j40aw3dvbOmW17e05Rka8jI97uP76Z3j5y6veRWLJ5s1p/P48+/cHeNnLFj6neQJY7h5j8zGLS1qnp1cfKbaS7u7sksA4k1FMTbllVJNYkZU9xrfe2ovXW+C1rx1n584U73vfdr7+9X7e9raRVZ87n4dvfrOfCy5ILMkwDw5mOHBg5Y7uormt1F/h7EoYIcTaaYVSassdd5RS/UqpDyil/kUp1TP3secrpbbatJZTwMZF/98w9zEhmtrUlNv2MmqA4eFZXK4Czzyz+ijxZNLBxIRnWUdqAIcD+vuzNRnZNDFhBEw9Pa1TVjs8PIvHU+DTnz6yZkExGPuKd+2a4cknl3amNk8AKw2Mz95jXO7rtKsrt6SUenzc+JlLKbVYSak9oImEgx/+sIurrpoiHM5z2WVR9u6d4mtfG+To0dUv3t1/fwenTnl5/etHl3x8eHiWSMRdswaDoj4yGUU261jW7FACYyHqI5eDRMJFZ2dz//239JdCKfVc4CngDcAfA2bHn73AP9i0loeBHUqprUopD/A64HabnluIupmaKj8TZ4XLZTTTKtWZ+sSJlTtSmwYGMjUppTaDpFYKjF//+jHuuONxLr88uuafe9euGZ56KkBu0UvJzPjascfYLKUuR1fX0oyxjGoSq3G5wO/PF22+9YMfdJNOO3nNa8bnP/YXf3ECn6/AJz+5mcIq29+/8Y1+hodnueKKpYMyhoaM16LsM24t5rFrcSk1GMc1symhEGLtmI1J10vG+Cbg81rr5wCLz67vAp5vx0K01jmMecl3AfuBm7XWv1VK/Z1S6hUASqnfUUqdBF4DfEUp9Vs7PrcQtTQ1VX7AYdXmzemSs4zNjtQrZYzBGNlUi8C4FTPGDgd0dJQfhNphz54ZZmcdSy6E2NV8q1Aw/qiV2zm9pyc7v4ceYHTUeL+/v3V+5sJe4fDKe0C1Nsqo9+xJLtmj3tOT48/+7CSPPhrme9/rWfE59+0L8JvfhHjd68aWdYYfGjJOWU6dkn3GrcQMflcKjCVjLMTaW2+B8XOBr6/w8TNAv12L0VrfobU+V2t9jtb6H+Y+9jGt9e1z7z+std6gtQ5qrbu11ufZ9bmFqJVK9m5atXVrmlOnvGSzxTsmmTOMN2xYOWM8OJhhfNy96nNUYnzcTTgs82ztsnu3sW9ycTm1GWCcfXJoRSiUZ3bWQTariMWc5POqolLqaNQ1/9qRjLEoxdjbvjxwefTREM8841+SLTZdc80kF18c4/OfH2ZiYnm2+T/+o59QKMcrXjGx7DazO7U04GotyaRx+iqBsRCNYb0Fximgc4WP7wJao92sEDVgBB2umuwxBiMwzufVfLn0So4d89HfnykaoA4MZNBazWf77DIx4W6pbHG9bdo0SzBoNOAyxeNOgsF8RfOTF+/3NMuhy80Ym5UQ5j7jsTE3wWB+2b4/IUxtbbkVA5dbbumlrS3H3r3L9+4rBX/918fJZBx8+tObltx2+rSHn/ykk1e9amLF111HRw6fLy+l1C2mWH8FCYyFqI/1Fhh/D/hbpZR59q2VUluAG4Bba7AuIVrC9LQ5w7g2BwpzZNNq5dQnTniLllFD7UY2TUy46e2VwNguDsfyBlyJxPKurFYtDozNcujyM8ZmYGw8fnTUIx2pxarC4Tyx2NKs78SEi3vu6eTlL58segFv06ZZ3v72M9xzTyc//Wn7/Me//e0+lILXvW7la/RKGfuMJWPcWsxS6mKBsZZCJSHW1HoLjD8AdAHjQAB4ADgMRICP1mZpQjQ/M5NWq4yxGfAWa8CltZEx3rSpdGBs98imiYna7a1er/bsSXLokH++dDked1Y0wxjODowru4BjVgRMTpoZY4+UUYtVrZTR++53e8jnFa9+9fIy6sXe9KYRduyY4YYbNpFIOEgkHHz3uz3s3Tu16r724eFZyRi3mIXmW8u7UhcKSrqQC7HG1ltgnANeCLwS+Cvg88DVWuvLtdbJ1R4oxHpmZtJqtcc4ECjQ358pGhhHo07icVfRjtTAfIbPzpFNWkvGuBZ2754hk3Fw5Ijx804knBU13gK7MsbG69osxR4bc8uoJrGqs5tv5XLwne/0csklMTZvLn6cAqOr9Uc+cozJSTdf/OIw3/1uD8mkkze8YfUdXWbGWLKIraNY8y3zeCjl1EKsrUjERSiUw7Xy0IGmUXL5SiknEAWerbW+B7in5qsSokWYmbhaZk63bk0VLaUu1ZEawOPR9PTYO7IpGnWSzTpkj7HN9uwxrkPu3x9k164U8bir4gyteQIZjxsZY6dT09ZWXpC9uJQ6lzMuhkgptVhNOGxkjAsFY3vAAw+0Mzrq4QMfOGHp8eefP8NrXzvGt77VT3t7josuii/pYr2SoaFZkkkn0aizbl3lhb1W60oNRmAs3fGFWDuRiKvps8VgIWOstc4DxwCpQxKiTNPTtc0Yg9GA6+hR34ozPs2O1Js2rZ6JsXuWsTmqSTLG9hoezhAO53jySaMBl50Z466uLI4yqw99Pk0wmGdy0sXEhButlWSMxarC4dySUtdbb+2lry/DZZdFSjxywZ/8yWkGB2eJRl284Q2jJe9vzjK2e7uIqJ9k0oHLVcDjWVoGsPi4JoRYO+smMJ7z98A/KqVWHiIohFjR1JQLr7dAIFC7Lr2bN6dJp52MjS3vKn3smA+nU8/P8ixmcDBjayl1K84wbgRKGeXUZmfqeNyu5luVjxTr7s4yOemWUU3CksWvuxMnvPz85+288pUTZZXfBQIFPvWpp3nzm0e47LJoyfsvzDKW6/utIpk0jn3qrCmDEhgLUR/T0+6WCIyt/in6ALAVOKWUOgks2Vestb7A7oUJ0QrMTNzZf7zttHWr2Znaz8DA0kD0xAkvw8OzJU86BwYy/PSnHfPljdUaHzdOQHt7JUiy2549Sb7xjX5mZ1VVGWOzBNEc11Rpuf9CYGxcDJFSarGahRJ+F3fc0YXTqXnVq5bPHy7l/PNnOP/81UuoTcPDRmAsnalbRyLhXHE8lwTGQtRHJOJixw5rx+RGZjUwvqWmqxCiRU1PV56Js8oc2XT0qI9LL40tue348dU7UpsGBzNksw6mplz09FS/XskY187u3TPkcg4efzxEoaAq7krtckEgkJ/PGJsXWMrV1ZXjyBEfo6Nmxlh+5qI4MzCemHBz++09XH55pOZbLkKhAm1tOelM3UKMwHj5RUEzMF7c4E0IUXuRSO3Pd9eCleZbbiAIfElrfaz2SxKidUxOumueNe3qytHWllvWgEtrY4/xc58bL/kci0c22REYj4+7CYVyRWeSisrt2WNckX3ooTCwfI5nOUIho0Pw9LS74pFiXV1ZHn44zNiYB58vX3EGW6wPbW3G8eU73+khGnXxmtesPqLJLkNDs5IxbiFmKfXZJGMsxNpLpxWzsw7a25s/MLbSfCsL/AlQw2JQIVrT9LSr7Nmw5VLKyBqfPbJpfNxNOu1ctSO1aXDQKDW0a5/xxIRbssU1MjCQoaMjyy9/2QZQVSAaCuUZG/MwO+uo+HXa3Z0lFnNx8qSXvr7abhsQzc8MXO69t4PNm9NcfHHpC3d2GBrKcOqUBMatIplcOWPs8xVwOvV812ohRO21ygxjsN58627gRbVciBCtRmuj+ValmbhyrBQYW+1IDUawBdjWmVpmGNeOUkbW2GzAVW3G2HydVPo67e42/hAeOBCQ/cWiJPNCjtaKV796fM0upAwNzTIy4pFZxsB737udr3+9v97LqEoy6Vjx2KeUcVyTjLEQa2c9BsY/AT6plPonpdSblFJ/uPitlgsUolnF405yOcea7LnYujXN1JSbaHThZODYMSNQtrLHOBQqEA7nJGPcJHbvnkFrI6KoNmNsXgyppvkWwOioR/YXi5LMLJ/XW+DlL59cs887NJRhdtbB5GQZ7a9bkNbwyCNhHnywvd5LqUqxjDFIYCzEWjNHk7ZCYGz1L8QX5/790xVu00DDHoFSqRQPPvhgvZch1qHR0Q7gQiYnn+TBBw/W9HOlUluADXz/+4fYtm0EgF/+8vm43cMcPnwfTz9d+jnC4c08+WSy6t8XrWF09EIymaPyu1cjSm0FXg7AoUMPE4mUHlmzknQ6jNbGCfLx47+iUCi/O/CpU/3AdgCy2ad58MFfVLQWsX60t+/k/POfYd++n63Z54xGNwObuPPOg/PHyPUomfSRzT6XgwedTX18jsUuJBI5seLXoNRGjh+v/m+ZEMKahx8+F9jBM888zMyM9Zn0jchSYKy1tmGAS30UCgU6OzvrvQyxDo2N9QIwOOis+Wvw3HPNTpwb6Ow0Sqenp/sYGIjT3W3tc/f3p5mY6Kh6rYmEh3zeSX+/lt+9GnnWsxbK4wcH/YTDlR2iOzoW3t+40UNHR/k/r3x+4c/I4KAcb0Vpn/jEnQSDGdzutXutbN1q/JtOD84fI9ejRMK4EBaPB3C5BgiHm+97kc06yOeddHY6VjzehMMFstmgHIuEWCNadwEwPOwlHG7u37umDXiFaHTRqB+AtrbKxuCUo7c3idud58yZhfK4kZEw/f3WG9v09CSYmAhWvZbpaePr7uxMVf1cYmWdnSna243vr99f+b5ev3+h9Dkcrux1uvj13dXV/DMMRe11dKRxu5fPoK2l3t4kAOPjoTX9vI3G/LsEcPJkc5ZTp1JG2ebi49difn92/j5CiNqLx30oVSAYbP4+I5YDY6XUy5RS9yulJpRS40qp+5RSL63l4oRoZrGYsce3vb32gbHDoRkYiHH6tNGpOJ9XjI2FGBiIlXjkgu7uJKmUh2SyuhOKSMQ48erokMC4VpSCrVsn8XhyuFyVdxMKBIw/YqFQGqezsufxeArzzyOBsWhUHk+e9vYUExPrOzA2j88Ap061ZmAcCGSYmZHAWIi1Eo97CYUyOFog3WrpS1BKvQ34DnAE+CvgQ8AzwHeUUv9P7ZYnRPOKxXwopQmF1qZUbWgoyunTxonOxESQfN7J4KD1wLinJzn/2GpEIka35M5OCZJq6corD3L11fureg7zxLLaizdm9loCY9HIensTjI9XXxXTzMzA2O3OcepUR4l7N6bSgXGWVMqeRpJCiNLicW/FVWeNxmrzrb8C3q+1/uKij31NKfUrjCD5321fmRBNLhr1EQrNVpyJK9fgYIyHHtpMJuNgZMTIHJdXSm0ExpOTITZvrrx5gnniZQZLojae/ezTPPvZp6t6DjPTW225f1tbmvHxUFPuVxTrR29vgsOHe+q9jLqKRPx4vVk2bow0ccbYCHpXyxinUm4KBVoigyVEo4vHfS3z99/qIWMTcOcKH/8hsNm+5QjROmIx35rsLzYNDUXRWjEy0sbISBigrFLqhcA4UNU6pqf9+P0ZfL7KxwiJtREI2JMx7u1N0NcXX7OZtEJUorc3weRkkHx+/b5QIxE/HR0phoejTRwYl95jrLVidlbKqYVYC0bGuDUCY6sZ4+PAXuDwWR9/CXDM1hUJ0SLqERgDnD7dzshIG4FAhrY26weqcDiN252veg+eeeIlGp9dGePrrnuUdFpOQkVj6+1NUig4mJoKzDfjWm8iET/t7WmGh6Pcd9/2pjyhtVJKDTAz4y56HyGEfRIJ75ptG6w1q4HxTcA/K6UuAszBcM8H3gS8txYLE6LZxWI+Nm+eWrPPNzgYRynN6dNt8x2py8ngORxGA67q9xhLYNwsFvYYV/fzamubLesijBD10NOTAGBiIrRuA+No1M+mTdMMDxvbZU6ebGf37rE6r6o8pTPGxgW/mRkP3d3S90CIWtLayBivZSKoliyVUmutvwK8FtiNESTfBOwC/khr/dXaLU+I5hWL+dakI7XJ48nT05OYzxiXU0ZtksB4fenoSOF05svaiy5Es+rtNQLj9dyAyzw+b9hgVBg1Yzn1QmC88miYxRljIURtzcy4KRQc6y5jjNb6OxidqYUQJWSzDmZmPGt+BW1wMMbx451MTga57LKny358T0+Sxx4brvjza210pZYZxs2hrW2Wm276nnSTFutCd3cSpQrrdpZxOu0inXbT0ZGis3MGvz/TlJ2pZ2bcOJ35orOwzYBZOlMLUXuJhBeg6bZkFLNqxlgp1auU+hulVNsKt7XP3dZdu+UJ0ZzMGcZrHRgPD0c5c6YdrVVFGeOeniTRqJ9MprJWnjMzHrJZp2SMm0hPz4x0bhXrgsul6eqaWbeB8eIZ80rRtA24Uilj73CxrULBoGSMhVgr8bhxvrsuAmPgz4CdWutlZ9ha6yiwA/jzWixMiGZmBsZrWUoNMDS08KtaWWBslBpOTlZWajg9bZ54SQZSCNF4enuT6zYwjkaNv0vmhctmDYzT6dWbai3sMZbAWIhai8XWUcYY+APg31a5/d+Ba+xbjhCtoV4Z48HB6Pz7AwPl7xvt7jZHNlUWGC/OSAghRKPp7U2s2z3GZx+fh4ejxGJ+4nFvPZdVNjNjXIy5x1hKqYWoPbOUOhRaH823zgGOrHL708BW+5YjRGswr8yvdWBsjmxqa0vNnxyUw5xlXGkDLvPES/YYCyEaUU9PgkgkQDa7/vYPLA+MFzpTN5NSgbHbncfpzEvGWIg1YJZSt8pkilJ/GbLAxlVu3wDk7FuOEK1hIWO8tgFiOJwhHE5XlC0G6OycQamCZIyFEC2pry+B1qrq7vvNKBLx43Tm57vHNmtn6lKBsVJG1nhmRjLGQtRaPO7F7c7j9bZGOFgqMH4UeNUqt78a+LV9yxGiNcRiPjyeHD5ffs0/98tf/luuvPJgRY91uTSdnamKTxqnpwP4fBl8vtY4QAohWsvCyCZ79hlnMg5++MNdfPvbF6K1LU9ZM8aopvR806pm7Uw9M+NZNTAGY8axOdZJCFE78biXUChdtBlesyk1rulLwM1KqZPAF7XWeQCllAt4D/CnwOtqu0Qhmk8s5qvbsPOXvnR/VY/v6UkyMVHZSaN54iWEEI2ot9fYLlJtYFwoKB58cAu33PJsJieN59q5c4wLLzxd9RprJRLx096+UM3TrJ2pS2WMAQKBjGSMhVgDiYS3ZRpvQYmMsdb6NuAG4HPAtFLq10qpXwNTwGeAz2itb639MoVoLrGYb8kJSDPp7k5Wtce4s1M6UgshGlNHxwxOZ77iwFhreOyxIT760Zfyla88n7a2WT74wZ/Q1xfnllsupLDyaN2GYFy4XPp3aWio+QLjUl2pwQiMJWMsRO3FYr71ExgDaK0/AjwP+F/AaeAMRjfqS7XWH6rt8oRoTkbGuDkPFD09SaanAxQK5dfFrHTiJYQQjcLhMKtiyr/4d/hwN5/85F4+85kXMTvr4j3vuZ/rr/8hF1xwhj/8w99w7FgXDz20uQartsdKx+cNG5qrM3U26yCbdVoIjLPSfEuINZBIeOf7FrSCUqXUAGitHwIeqvFahGgZ0aiPLVum6r2MivT0JMnnHUQifrq6rGd/tTbmGEtgLIRoZMbIJusZ4zNn2vi///fZPPzwZtrbU7zlLQ/xwhcewuVa2FR86aXH+MEPzuPWW5/N7/zOcZzOxtpwnMs5SCSWVzIt7ky9e/dYPZZWlnTaCHYDgcyq9zP2GEsptRC1Fo+vo1JqIUT5CgWjfX299hhXq6fHaE5TbkZlZsZNNuuSwFgI0dB6e5OWA+NDh3r48IdfzhNPDPHqV/+Gm276HldeeXBJUAzgcGiuvfY3jIy08bOfbavFsqtijhA8+/g8PNxcnanNLLCVUupkUjLGQtRSPq9IJr2Ew815vrsSCYyFsNnMjId83tHUe4yh/MA4EgkAMsNYCNHYensTxOM+0unSRXM/+MF5BAIZbrrpu7zylU+s2nH/ootOcs4543z3uxeQyTTW6VWxUXpdXc3VmdrcN+zzle5KnU57KtoSJISwJpEwqjIkYyyEKMq8Mt+se4wrD4xlhrEQovFZHdk0Ohri17/ewItedIj29tLHc6XgNa95jMnJIPfcc64ta7VLseNzs3WmNgNjK3uMjftb2jEohKhAImGc70pgLIQoKhYzA+PmLC3x+fKEQmkmJ8sLjKenzRMv6UothGhcC4Hx6se4u+7ahcNRKGsu/HnnjXLeeWe4/fbzGyooW+3CZTN1prYaGPv9mbn7yz5jIWrFbNongbEQoqiFwLh5M6eVdG2VjLEQohmYfRRWyxgnk27uv/8cLr30aNnHtGuvfYx43Mddd+2qap12ikT8KKVpb19+wbaZOlObgbGZES4mGDQCY+lMLUTtmMeMUKg5E0ErsXQ5Uyl1L7BSi0UNpIHDwNe11o/auDYhmlKzZ4zBCIxPn24r6zGRiB+fL4vfX3wPnhBC1Ftb2yweT27VwA7EvPIAACAASURBVPi++7YzO+vmqqsOlP3827dPctFFJ7jjjj1ceeVBQqHVOygDjIyEue22C3jlK59gaChW9ucsJRLxEw6nV+yW3Uydqa1njM1SagmMhaiVeHz9llLvBy4ChoCTc2+Dcx8bAy4DfqmUenEtFtnKjh7t5HOfu5wzZ8L1XoqwSSzmQ6kC4XDpk6FG1d2dZHIyiC5j4ojMMBZCNAOlVh/ZlM8r7r57J7t2jbJly3RFn+Paax8jnXbzgx+cV/K+Dz+8kY997Pf5+c+38thjwxV9vlJWOz43U2dqszTa6h7jmRkppRaiVtZzKXUa+N9a611a6zfPve0G/h2Y1FpfBHwZ+EStFtqqslknjz66kbExCYxbRSzmIxyexeForDmW5ejpSTI7657vOGjF9HRAAmMhRFNYLTB+5JGNTE6GuPrq/RU//8aNUX7v957hRz/aOd9/4Wy5nOKb37yIL3zhcgYHYzgcBZLJ2gRy0WjxwLiZOlOnUm6czgJud37V+5l7jCUwFqJ24nEvPl8Gt7tQ76XYxmpg/BbgSyt8/CvAW+fe//+APXYsaj0xR9sU+8Mpmk802rwzjE2Dg0Yp38mTnZYfIxljIUSz6O1NMDGxclXMXXftoq8vznOec6qqz/GqVz1OPu/ge987f9lt09N+PvWpvfzwh3u48sqn+OhH7yYYzJBI1GafbyTiX3F/MTRXZ+pUyo3fn0WVmMK0kDGWUmohaiWR8LZUthisB8YKWKkeaM/cbQAZoHUuGawRc9atOQNWNL9YrPkD43POmQDg4MFeS/fX2jjx6uyUjtRCiMbX25sklfIsy9AeOdLNoUN9vOQlB6qu+unvT3D55Yf56U93MDa2kJ1+8sl+PvrRl3LsWCfvetcDvOUtD+N2FwiFZmuSMS4UFNGob9ULl83SmdoIjEtvU1roSi2BsRC1Eo+v38D468DXlFIfVEq9cO7tg8C/Af977j6XA/tqsMaW5nYXCIfTkjFuIbGYr+iV+WYRCmUYHo5w6JC1wDiVcpPJuOYv9AghRCMrNsv4zjt34/dneMELjtjyeV75yidwOArcdtsFFApw++3n8Y//+GJCoVk+/vE7ufTSo/P3rVXGOB73UCg4Vg2Mm6UztZkxLsXjKeBy5aWUWogaisd9hEKtFRhbHbL3AWAUeB8wMPexEeBG4Ka5/98F/NDW1a0THR2p+VE3ovm1Qik1wI4d4zz00CYKBXCUuIRmXtgxtwYIIUQjWxwYb906BcDUVICHHtrEVVcdsK27fmdnir17n+KHP9zD1FSA/fsHeN7zjvLHf/wLfL6lnyMUmq3JuYCVUXrN0pnaamAMEAhkJGMsRA3F416GhqL1XoatLGWMtdZ5rfU/aq2HgA6gQ2s9pLW+QWudn7vPca31yVoutlV1ds4wPS2l1K0gk3GSTntaJjCemfFy5kzp8jqZYSyEaCYrZYx/9KNz0Rr27n3K1s/18pf/Fq83y8GDvbz5zQ/xrnc9sCwohtpljKNRK4Fxc3SmLi8wzkrGWIgaise9LXG+u5jVjPE8rbX9A/bWuY6OFCdOWG9yJBpXLGac1LTCgWLHjnEADh3qnT9pKsbcIy8ZYyFEMwgEsgSDs4yPBwFIp53ce+8OLr74BL29SVs/Vzic4cMf/jFud4GNGyNF71erPcZWLlw2S2fqVMo93xyyFL8/K823hKiRTMbJ7Ky75Uqpre4xRin1VqXU3UqpA0qppxe/1XKB60FnZ4pIxEehUKLNomh4sZhxAtIKgfHAQJxwOG2pAZdkjIUQzaanJzmfMX7ggW0kk16uvvpATT7Xtm1TqwbFYGSMUykPuZy95wJWjs/N0pm63FJqyRgLURtmdcu6bL4112jrM8CvgC3AdzEabXVhzDIWVejomEFrB7GYr95LEVUyf4atEBgrZWSNrTTgmp724/Vm8fmsnbAIIUS9GSObQhQKcNddu9m2bWK+UqYezMyL3VnjSMRPIJDB41l99m8zdKYuJzD2+7Oyx1iIGjEb9a3LwBh4O/AOrfWHgSzwRa31KzCC5c21Wtx6IbOMW4dZSt3sXalNO3aMMzLSNv91FWPOMC41W1IIIRpFb2+C8fEgjz8+zMhIG1dddaCux7BQyBgxlEzau8/Y6oz5Ru9Mncs5yGZdZWaMJTAWohYWAuPWON81WQ2MNwAPzb2fAtrm3v8W8Gq7F7XeSGDcOswmJ61yoDCzJ4cPr541tnriJYQQjaK3N0E26+Lmmy+kszPJJZccq+t6gkEj85JI2J8xtjJKb3Fn6kZkZn/LyxhLKbUQtRCPGxWS63WP8QjQM/f+MeDSufe3A9ruRa03HR0zwEIDI9G8YjHfXEnx6iVrzWLr1imczjyHDvWsej8JjIUQzcbsTH3iRCd79x7E5arv6Uy9M8aN3pm63MA4EMiQTrulf4sQNbDeS6nvAV4x9/7XgM8qpe4Fvg3cVouFrSft7WmU0pIxbgGxmK9lyqgBPJ48W7ZMcfBgX9H7aA3T0wHpSC2EaCpmYOzx5LjiikN1Xs1CxtjOPcZaG5VMVgLjrq4ZfL7G7UxdfmCcXfI4IYR94nEvSun5C3qtwuq4pncwF0Rrrf9VKTUNPB+4FfjXGq1t3XA6NW1t6fnOkaJ5RaO+lmi8tdi5547z4x/vJJdz4HIVlt2eTrvJZFySMRZCNJWeniQuV57LLjvSECd35hrsnGWcShnHZyul1I3emXohMLb2swoEjPvNzLgJBuv/8xWilcTjXoLBWRyO1ioctpQx1loXtNa5Rf//ttb6TzH2GL+jVotbTzo7Z5iellLqZheLtV5gvGPHONmsk6NHu1a83ax0MLcECCFEM/B681x//Z1cd92j9V4KYAR8SmlbM8bljtJrjsDY+h5jQEY2CVEDiYS35cqooYw5xkVsAP7ZjoWsdx0dKckYt4DWDIwnAIqObZIZxkKIZrV58zReb2P0hHA4jFnGdmaMyz0+N3JnarPDdLml1NKZWgj7xeMSGIsa6uxMyR7jJlcoGAeKVguMOzpS9PbGizbgMl+3ssdYCCGqEwzO1jlj3LidqcvPGGfmHicZYyHsFo/7Wq4jNUhg3DA6OmaIxfzkctI9sVklk14KBUfLBcZg7DM+eLAPvcJWEskYCyGEPeqdMW7kztTptGSMhWgUkjEWNWVm28w5uKL5xGLGTLdW6kpt2r59nGjUz/h4cNltkUgAjydn+WRFCCHEykIh+zPGbnduPkgspZE7U6dSbhyOAh6PtdJ3s/mWdKUWwl5am4Fx653vrtqVWin1/hKPH7JxLeuaGRhPT/vp7q5PE6PTp9v42teex1/8xb2W/4iKBdGoERi3YsZ4x45xwNhn3NeXXHKbOSNTSbGDEEJUJRjMMDLSZtvzlXt8buTO1KmUm0Aga/lrWcgYSym1EHZKp93k886WzBiXGtf0XgvPcdyOhax3ZkffSCQATNZlDYcP93DwYB+nT7ezfftEXdbQzMyMcSsGxhs3RvH5Mhw61Mvzn390yW3T0346O6UjtRBCVKsWGeNyt7kMD0d57LFh29Zgl5kZDz6f9Yv2LlcBtzsngbEQNjOb8627wFhrvXWtFrLeLc4Y10syabzQG7EbZTNo5VJqh0OzffvEip2po1E/mzdP1WFVQgjRWoLBDDMzHgoFZct80GjUP99Qy6oNG6Lcf//2httDmEq5y96yEwhkZY+xEDZr5cBY9hg3iHA4jcNRqOvIJvOPhwTGlYlGfShVIBhsvQMFGOXUJ050LNuvNT1dfkZCCCHEcqHQLForkkl7grlIxFdBxrgxO1NXEhj7/dmG22NcKNR7BUJUx4wTQqEWTATVewHC4HAYXSOnpwN1W4NZviWBcWWMGcazOFr0t2rHjnG0dnD4cPf8x1IpF7OzbgmMhRDCBsGg0TDKrOCqRibjZGbGW/bxeWgoBsCZM40VGKfTlWSMMw1XSv3JT+7lm9+8qN7LEKJi8bhRISkZY1FTHR2pOmeMjT8edo6KWE+MwLj1rp6Ztm+fRKnCknJqY0+8zDAWQgg7mHNBE4nqg7lIpLLtPV1dSdzuPKOj4arXYCej+VamrMc0WsY4EvHz1FP9HD3aVe+lCFExM4HW1iaBsaihzs6ZOu8xNjPGvrqtoZm1emDs92fZuDFyVmAsM4yFEMIuoZB9GeNKj88OB/T1xRkZaazAeGam0oxx4wTG+/YNADKaUzS3eNyL05kvqxles5DAuIEYGeP6lVKbGWMppa5MqwfGYJRTHz7cQ6FgzMswL+SYXdWFEEJUzuxRYUfG2Ay+Krlw2d8fb8iMcbkn4oFAllSqcUqpf/tbIzCuZxJEiGolEkZjvlYc0ymBcQPp7EyRSHjJZOrzYzEzxlJKXZlYzNeSHakX27FjnHTaw4kTxt4zyRgLIYR9GiFjDEZgPDYWbphGUbmcg2zWVVHG2M7xV9XQGvbtGwQglfKQTjvrvCIhKtNoHevtVFUEppT6ulLqJ3YtZr0zZ8HWa5+xNN+q3Oysk3TavS4yxsB8OXUk4sfjyREItF45jRBCrDVzD609e4z9OBwFwuHy/y4NDMTJZp1MTVVexXbPPdu5/fbzKn78YqmUMV20kq7UmYyLXK7+qa3Tp9uJRALs3DkKSDm1aF7xuG++H0KrqTY1qWx4DjHHvKpbr3JqKaWunDnDuNUD497eJB0dMxw+vBAYd3SkWrKcRggh1prTqeeynPZkjNvb0xVNSujvNzpTj462Vfz5f/rTHdxzz7kVP34xs4FWuRdhzQsNjdCAy9xf/D/+x9MAdZ1CIkQ1JGNchNb6zVrrK+xazHpndvatx96TbNZBJuPC5cqTTHrn95AKa8zAuNVLqZUyssYHDxqB8fR0QMqohRDCRsHgrC3lv+aFy0r098cBKt5nXCjA6dNtTE0FyOWqz5+YgW0lGWPj8fUvp963b5CBgRg7dkwA9asOXO+efrqr4WZ0NxsjMG7N811LRyul1JuVUssuXyqlPEqpN9u/rPVpIWO89gdLM1vc15dAa9Uwe3KaRTS6PjLGADt2TDA+HiYS8Vd14iWEEGK5UChjS68PI2Nc2fG5q2sGtztXcWfqqakAs7NutFZMTAQreo7FzMC2/D3Gxv3r3Zk6l1Ps39/Peeedmf+bKQ246uNLX7qMb31L5khXqlBQJJOSMf5fwEqXV8JztwkbhEKzOJ35upTXmIFwX59xlVjKqcuzXkqpAXbsGAPg0KEeIhH//N54IYQQ1bMrYxyNVn7h0hjZlKg4Y3zmzMIp4/h4qKLnWKzSjPFCKXV9L/YfOdLD7Kyb888fIRDI4HbnJGNcB5GIn7GxsJSxVyGZ9KC1WveBsQL0Ch/fBETtW876ppRRTl3PjPHAgATGlVhPgfGWLdO43TmeeGKIdNotGWMhhLBRMFh9xjifV8RivqqOz9WMbDp9emFv8thYPQNj+zLGY2NBvvCFyypqjLZv3yBKFdi9ewSl6j+ec706dKgHWDhnE+Uz44NWDYxdq92olHoCIyDWwH1Kqdyim53AZuCO2i1v/enoSNWlvMa8Om3uK5LAuDyxmA+fL4PHk6/3UmrO5SqwbdskjzyyEZBRTUIIYadQqPqMcSzmQ2tV1fF5YCDOE08MUShQdgOv06fbCQRmyWRcdc0Y+/1Gxti8+F+N//qv83j44c2cc84EL3vZ/rIeu2/fINu2TRIMGus3kiASnK21gwf7AIjFvBW9rsVCfBAKtWYiqNRL4hbgVoyM8X/NvW++fQN4O/DGWi5wvensnKnLVUTzj4bZiTKRkAN2OWIxH21trXn1bCU7dowTjxuvEQmMhRDCPkbG2FPVDGGz8qzSPcZgnA8YI5vK3yN8+nQ7w8NRenqSNmeMM2U9zq6McTLp5oEHtgFw333b0SvVUBYxM+Pm6ae7Of/8kfmPtbdLxrgezMahWjts2ce/HpnnfusyY6y1/jiAUuoo8J9a69b8LjSQjo7U/AD4tSQZ4/JpDcePd/LAA9v4zW+G2bAhUu8lrRlznjEsdFMXQghRvVAog9YO0ml3xTPizcC42lJqMDpT9/Qky3rsmTNtPPvZp/D5ckxM2BMYOxyFsquyzEC62j3GDzywjUzGxd69B/jRj3Zx8GAvO3eOl34gsH9/P4WCg/POOzP/sc7O+pzrrWezs06OHeuiry/O2FiYaHR9JTTs0uql1FaLCO4A5jeMKKWepZT6hFLqOjsXo5S6Win1lFLqsFLqQyvc7lVKfXvu9l8qpbbY+fkbQWdnilTKQzq96jUL25lXUzs6Ung8OQmMVzE97ee//ms3H/nIy/joR1/Gj350Lnv2jHDddb+q99LWjDluAiRjLIQQdgoGjRPOajJadgTGZs+RcjtTJ5MeolE/Q0PRuSDEnsDY78+iypwk6XJpPJ5cVRnjQgF+/OOd7Ngxxh/90a/x+TL89KfbLT9+375BvN7ssr+bxrmes+J1ifI8/XQ3+byDiy8+DkAsJs3PKtHqgbHV6Otm4P8A/66U6gHuB04D71VKDWmtP1PtQpRSTuBLwF7gJPCwUup2rfWTi+72x8C01nq7Uup1wA3Aa6v93I3E7PAbifjn/yithWTSi9udw+MpEA6nJTA+y+ysk1/9aiMPPLCNffsG0NrB9u3jvOUtv+R3f/cY4XB55V3NLhyeZWAgxuRkYL7rpxBCiOqFQsYxNZHw0NdX2XMsBMaV7wPs7DRGNpXbgMtsvDU0FAOM0S7JpHt+f20lzMC4En5/dr4UuxL79g0yMtLGq171OD5fnt/7vaM88MA23vjGRyx9Tfv2DbJr1xgu10JtvHmuF4368fkSFa9NWHfokFFG/dznnuSOO86TBlwVSiS8eL3Zlu2pYzUwvgD4xdz71wKHtda/o5S6BrgRqDowBi6Ze96nAZRS/wlcAywOjK8Brp97/xbgi0oppXU5uz0a2+L5dmsZGM/MuAkGjT/G4fCs7L1Y5PHHB/nnf34B6bSbnp4Er3jFb3n+859mcHDtfj6N6MILT3HwYG/ZV/CFEEIUFwoZmZhksrqMcSiUXhKMlavSkU2nTxujmoaGomSzRkZ0fDxEMDhd8VqqCYyDwUxVzbd+/OOdtLenuOQSI9P4whce5p57zuXnP9/KlVceXPWxExMBRkbaeNGLlt7PPNeLRPz090tgvBYOHuxjeDjC4KAxTCcalcC4EvF4684wBlBWYkql1AywS2t9XCl1C/AbrfXfK6U2Age11lXXIyilrgWu1lq/be7/bwJ+V2v9nkX32Td3n5Nz/z8yd5+Js57rHcA75v773GrXJoQQQgghhBCi6f1Ka33xSjdYzRgfAv5QKXUr8BKMLDFAP9BwHYe01l8FvgowPDysb7jhhjqvyLpk0s073/larrvuV7z0peWNA6jGpz71YrJZJx/72N18+cvP58iRHj7zme+t2edvZDfddAWRiJ9PfEImkwkhhKitaNTHe95zLW95y0MlM5LFXH/9Vfj9Wf7qr+6pai3f+tZzuPvuXXzta/+Jw2GtOO8zn3khk5NBPvnJ/yKZ9PDOd/5R1ec0H/vY79PWluYDH7i37Md++tMvIpn08PGP31n2Y7/1redw5527+dznvkNX18J+7R//+Fy+/vVL+Lu/u4OtW6eKPv7LX34+Tz45wD//861LqqvM78sb3vAIV199oOx1ifKcPNnOhz/8B7zjHQ9y2WVP86d/+oc861mnefvbf1H6wWKJv/3bqwkGM/zlX1Z3bKmnN73pTUVvs9p86+MY+3mPAr/QWv9y7uNXAb+uZnGLnAI2Lvr/hrmPrXgfpZQLaAcmbfr8DSEQyOLx5Ob3B62VmRnPfPdLKaVeamwsRF/f+i6bFkIIsTbMbU2JROXlv5GI35bGiP39cXI5J1NT1kcLnTnTxtCQUa4aDGYIBGarbsBVjz3Gs7NO7rtvOxdffGJJUAxw6aXP4HbnVm3CVSgY+4vPP//Msi1HgUAGtzvP9LQ0gFoL5pgmc6JGW1ta9hhXqNVLqS0Fxlrr24BNwMXA1Ytu+jHwfpvW8jCwQym1VSnlAV4H3H7WfW4H3jL3/rXAPa20vxhAKWPvyVoHxsmkZ8ke45kZD7mcbB4tFBTj4yH6+mQPkBBCiNpzuQr4fNmK9xhrbTR1siMwLrczdSbjYGwsxOBgbP5jvb1JxsfrFxgHApXtMf7FL7aQTHrZu/epZbcFg1kuueQ4P//5lqKdpU+c6CQe93H++WeW3Wac680QjUpgvBYOHeolHE7PjyBra0vL975CRmBceVO/Rmc1Y4zWelRr/WutdWHRx36ptbalBuT/Z+/Og+O6rzvRf3+9o/fGDgIEuIKUqM2UKMmKZcqRNLFiJ5Kd8kte3iROOeMkNX6VVMbJi10zyeTF9ZK4Ms54XM68SiYvFWVxxfF4xlEWO5E1sSg52kiKkkhJBCiSWAgQSwNo9L7+3h8Xv8bC7sbt/Tbu91PFItDrbeCi+557zu8cKWUOwP8J4B8BvAPgr6WUl4QQvyWE+NGNm/1/AHqEEFegBeS3jHTaC0KhBFZXWzv4PZFwFEdEeL3aDs+sMbCy4kYuZ2XGmIiIWsbjSdecMY7FHMjlrG0JjBcWfJDSUswYA0B/f7StgXEtGWMpgWefPYaRkVUcO7ZY8jYf+tAkkkkHXn11rOT1Fy8OAgBOnLhZ8vpgMMmMcYtMTPRjfHyxmLkPBJLMGNcgm7UglXIwY1yOEGK/EOJPGrUxUsp/kFKOSykPSyn/n43LfkNK+czG1ykp5SeklEeklPerDtZ7TaszxoXCraXUADiyCcDCgvZhzq6RRETUKl5vpuaMcSNmGCvBoDayaXFRX2C82ZF6e8Z4edmLQo0NsnM5gUzGhq6u2kYDut0ZZDK2qqrgrlzpxdRUNx5/fKLs5IXx8SUMDq7j+edLl1NfujSE4eE1hEKlfw/asV5rkyBmFIm4sLjoK5ZRA5ul1Hur5rT5VMKMgXF53dgsbaYGCYW0s4it+oNNpeyQUmwrpQaAWIxn09TBADPGRETUKh5PGvF4bRljFRgHAvWXO1os2jrjmzf9um4/NxeAEBKDg1sD4yiyWWvNJ/xTKS3bW3sptXa/ZFL/z/PZZ4/B7c7goYeulb2NENropomJfty4Edh2XSZjweXL/SXLqJV2LJszI7W+eHx8e2CczVrrmm9tRiphtpdLqSt2pRZC/PQu9x9t4LbQhmAwgXTajlSq9tKhaqgPX7d7e2DMjLHWeMtqzaOnJ9HuTSEiIpPweDK3BFt6qbWTjcgYA1o5tcoE72Z+3o+enjicznzxMtWjY2nJe0sTKz0SiXoD40zxcfRkutbWXHj11VE89tgEXK5cxdt+4APv4RvfuAfPP38YP/mT54uXT072IZOxlS2jBrQkSCLhQDpt3fbzosaanOyD3Z7HgQOb3cPVSaNIxFU8cUK7U3GBmrW+F+02rulPASQAlMtd1ptxphJU2c3qaldLAmPVlGJnxpiBsbZeqq8vrntMBRERUb2MUkoNaBVTFy4Mo1AQu34Wzs0Ftq0vBoC+vs3A+NixpVJ3q0hl9epZYwxAdwOu733vKPJ5q65RWYFAGidPzuDFFw/hE5+4ALtdqxe/eHEIVmsBx48vlL2v+v2srXVxuVYTTUz04eDBcPF3A2wGxuvrLgwNsSJQr2hUqyQ1cyn1HICfllL6Sv0D8AMt2EbT2RoYt8LOjLE6E8TAWCulZhk1ERG1kmq+VcuSqrW1Lrhc2V2znXoNDmojm8LhyuthCwU1qml92+W9vXEIIWse2dSoUmqVea4klxP4X//rKO6660ax8dhuHnnkCqJRF86fHyledunSEI4cWUJXV/nfQTCoVaKxnLp5Mhkrrl/vxvj49gZqfr92nM0GXNUxQyn1boHxOQAnK1wvAXCmT4Ntvlm2pinDzoyxzVZAV1fG9F2ppVQzjHkml4iIWsfrzSCftyKd3q2w71aNmmGs6O1MHQ57kMnYbskY2+0FhEKJmjtTq7XBtWeMM9sep5Jz5/ZjddWNxx/fPVus3HHHTfT0xIozjaNRB65f765YRg1sJkEYGDfPtWvdyOet2xpvAVqmHwBHNlVps5S6tkZ4nWC3wPg/Afh+heuvAPhQ4zaHgM3ymnZljAGtTEKVTJhVLOZEMulgxpiIiFpKjU+sZWTT2loXAoHGBcZq9uvCQuUGXPPz2vU7A2NAK6euPTDWMr21rgWtJmP83e8eQ19fFHfdNaf78S0WiQ9+8D1cvLgPi4sevPPOIKQUFRtvAVuP9diZulkmJvoBAEePLm+73OdLQQiJSMTcx7nVisWc8HjSsFr37vLCioGxlPIFKeW3K1wfl1I+3/jNMreurhxcrkzLziLuzBgDWjl1rTMU9wqOaiIionZQGZlaKrcikcZmjIPBBByOHBYWKmeMVbOwnaXUgBYY11pK3ajmW7t1IJ6ZCeLddwfw6KMTVfcVOX36PQghcebMEVy8OISurgwOHQpXvI/Hk4HdnmfGuIkmJvowNBS5ZU2s1Srh9aZZSl2laNS1p9cXA2yeZVjayKbWnEWMxx0QQsLl2vzQYcaYo5qIiKg9VMa4lgZcjS6l3hzZVDkwnp8PwOtNlTxw7uuLYW3NjWy2+sNOFdC6XLWVb+ptvvXd747Dbs/h9On3qn6Onp4E7rxzDmfOHMZbbw3httsWds2qCQEEAhzZ1CyFAnDlSt8tZdSKmmVM+kWjzj3dkRpgYGxYrZxvF4874HZnYNmyN3i9adM339oMjJkxJiKi1lEHn9VWbqVSNqRS9oYGxoAWGO+WMZ6bu7XxltLfH4OUAsvLnqqfO5m0Q4hCzSONrFYJpzNbMjCOxRw4c+YQfv/3H8Hzzx/B+99/veb1kx/60BWsrrqxvOzdtYxaCYUSLVs2Zzbz837EYs5t84u38vtTLKWuUizm3PMZ4+q7OlBLhEJJTE72tuS5EgnHtvXFgJYxNnvzrYUFL0KhBBwOzhckIqLWUcFZtRnjwWYGGQAAIABJREFURo9qUgYGonj99cojm+bmArj33pmS120d2VTteJxk0o6urixEHa1e3e5ssSR7ba0LZ8+O4OzZUbzzzgAKBQt6emJ47LHLePLJt2p+jnvumYXfn8T6epfuwDgYTNY8r5oqm5zU1heXC4wDgRSuXetu5SZ1vPV1J8bGVna/YQdjYGxQwWACa2tuSIm6Pgz0iMcd29YXA1pjglTKjkzGAoejUOaeextHNRERUTuoz+RqM8bNCowHB6PI561YXnajvz9+y/XRqAPRqKtixhhATeuMk0l7zY23lK6uDCYm+vFbv/WvcOVKH6QUGBxcx0c+8jZOnZrGgQMrdR9r2WwSTzzxDl5/fUT3qKdgMIlLl4bqe+ImW152o6cn0fRj0UabmOiDz5fC4GDpfTIQSDJjXAUpgVhs768xZmBsUKFQEtmsFfG4o+lt0RMJ+y2B8WYZlxPd3Y39gO0Ui4te3HmnvrO+REREjeJw5OFw5GrOGDeyKzWwvTN1qcB4fl7Leg4N3dqRWm2P3Z7H0lLlcuxSUil7zY23lO7uBC5e3AenM4ePf/wNnDo1g337Ig0P9j760bfx0Y++rfv2wWASiYQD6bS15lLxZrpxI4DPf/6j+LVfe27X8VNGMzmprS8u9zv2+1NIpRzIZKysDNQhnbYhm7UyMKb2CIW0Wcarq11ND4zjcQeCwe0fZmrHj0bNGRin01asrbmZMSYiorbweKqfDtG8Umot67aw4Ct5wnhuTnWkLh0YWyxqZFP1a4wTifoD43/7b7+PdNqG3t5bg/p22jrL2IgTMCYneyGlwMKCr6MC40jEiZs3/Th9+krZ2/j9qY3butDXZ6z9wohU3yGfL9XmLWkuNt8yKPWhtrbW/M7UiUSpUmqVMTZnmYkq9zLiBxUREe19Xm8G8Xj1gbHNlm/4CfVQKAmHI1e2M/XcnB92ew69vYmyj9HbGys2taxGMunYNjWjFj5f2nBBMaAtmwNg2M7U09MhAOi47s2Tk30Ayq8vBrQ1xkDnvbZ2UYFxs5N17cbA2KDUWcRWdCvUulJv/9DZmjE2I45qIiKidvJ4MlU3wVSjmhpdIixE5c7Uc3MBDA2tV5z/299fW8ZYNd/aizaTII0/1rt504crV+pr4jo1pTWnWl/vrGPBycl+2Gx5HDhQfpa0Coy5zlgfNTatq4uBMbVBM98st8pkLMhmbcWZiYrXq71hMDBmYExERK3n9aarzhgvLDSvaWTlwLj8qCalry+GRMJZ9WtqRPMto9paSt1o3/zm3fjyl09DVh6nXFahAExPBwF0XlZ1YqIPBw+GKzaPVaXU6+vGzNbrtbDgxV/+5b3I5ZrbHS2VUoFxrqnP024MjA3K4cjD40ljdbW5pdRqrt/ODx1VKmHWwHhhwQu3O7PnS0aIiMiYPJ5M1c23FhZ8TVsCNDi4jsVFL/L57QfgmYwVy8veso23lK0jm6qxlzPGHk8Gdnu+Kcd6kYgLkUgXVlZqe+ylJS9SKe0YsZMC40zGguvXu3H06HLF2/n92kmJTsuG7/Taa6P4znduw8WL+5r6PCpjXO+yBqNjYGxgwWCy6RljFRjvXGNstcqNxh+d/YZRKzWqqdPGExAR0d5QbfOtRMKOaNRV7CDdaAMD2simcHh7OfT8vA9SCgwPVw6MaxnZlMsJZDK2PRsYC6F17G7GsZ46frt2raem+6v1xb29sY4KjK9d60EuZ8XRo4sVb+dwFNDVlUEk0tkZ4+Vl7e/x5ZfHmvo8mxnjvfm3qDAwNrBQKNH0NcaqpMntvjUz6vOlEY12zpthIy0ueosf4kRERK3m9WaQzdqQyVh13V4tAWpmYAzglnLqzVFNu5dSA9VljDcPxvdu9VazkiCq4u/q1doC4+vXu2GxFHD77Tc7KjBWjbeOHi3feEvx+1Mdv8ZYnag6d26/7veKWqRS2iAjZoypbbQ3y9aUUu/MGAPa+iYzllLn8wLLy16uLyYiorZRvT/0Zo0XFrSAs1mfXYOD2uPu7Ew9NxeAEBKDg5UDY7c7C683XVXGeLPhz949GG9GEkTKrRnj7poeY3o6hH37IujpSSAWc95SQm9UExP9GBxcRyCw+7zdQCDVUUF/KcvLHvh8KaRSdly4MNy050km7RCisOdnPjMwNrBQSDuLWCjfO6Buu2WMO7WUWkrtbOczz5zA7GygqvuGw27k8xaOaiIiorZRPS70fg6rTG6zAuNgUBvZtDNjPDfnR19frGKjI0WbZczAeKtmZIxTKRtyOSuEKODatZ6aGnBNTYUwNrYKvz8FKUVHHA9Kqc1e1pMtBrSMcacHxuGwB/ffP4VAINnUcupUyo6urtyeX2Joa/cGUHmhUAL5vAXRqFPXma9aqMC4VMbY50thairUlOdthlxO4PLlfpw7tx/nz+8vlpfMzITwmc+8qPtx2JGaiIjaTWWM9TbgWljwIRhMwOVqTkan3MimubkA9u2rvL5Y6euLFdeu6qGaUpU6RtkrgsEkEgknMhlrw7JxKog9cmQZk5P9WFz0VnWyf33didVVD0ZHV4vdmyMRV3HEkVHNz/sRi7kqzi/eKhBI4t13+5u8Vc0Tj9uRTDrQ3x/D/fdP4XvfO9K0ZnXJpH3Pl1EDDIwNbXNkk7tpgfFmV+rypdRSwrBniFIpK956ax/OnduPCxeGEY87YbfncOed8/j4x9/Aa6+N4vLlvqpeAwNjIiJqt82Msd5Sal/T1hcrg4PrmJnZDGwLBYGbN3244455Xffv64vh/PkRFAqARUfN4oULw3A4cjh8uHKH4U62dWRTo3qbqGVwd901j8nJfly92lNVYKxOXoyNrcBq1dLNnZBZ3VxfXLnxluL3pxGLuZDLCdhsNc61aiPVeKunJ44jR5bw7LPHce7cCD7wgWsNf65Uau82wduKgbGBqTfL1dUujI2tNuU54nEHHI4c7PZbS6B8vjSyWRvSaWvTzkDX4x//8Ri+/vX3Fecwv+99s7j33lncccdccXszGRsuXBjB0pIH/f1xXY+7sOCFzZZHd3eymZtPRERUltdbfcb4rrvmmrlJGBiI4vz5/cjnBaxWieVlD7JZm+6McX9/DLmcFWtrbnR3JyreVkrg9ddHcMcd83A6jXcM0igqCbK62rjAWGWMjx9fgN2ex7VrPXj/+6d0339qSluXPDq6WmzC2gmB8fnzIwgEkrs2glPUyKZYzFX8PXQSVRnZ2xvHwYNh9PTE8PLLB5oUGDNjTG0WDGofGs1swJVIOEpmiwEtMAa0NwyXS19Q2Upnz46iuzuBT33qFRw7tlg8q7nVsWPaWcOJiX709+t7o1hc9KGvLwaLpfPOHhIR0d5QTfOtVEoLNpudMdZGNlkQDnvQ3x/D3JwfALBvn75ARHWmXlz07hoYT011Ixz24OMff6O+jTa4zWO9xq0zVhnjQCCJ0dGVqjtTT02F0NMTh8+XKVbbGT0wXltz4cKFYTzxxDu6qhEAFEvDI5HODox7euKwWIAHH5zCd75zG6JRB3y+xi4/0Eqpcw19TCNi8y0DCwa1P9hmjmyKxx1l1+6owNionalXVtw4eHAFt9++UDIoBoDh4TV4PGlcvqx/DQlHNRERUbs5nXnYbPliL5BKmj2qSdnZmXpuTo1q0psx1u6vpwHXuXMjEKKAe+65UcumdozNZXONO9ZTGWOfL41Dh8KYmupGoaB/Tdz0dAijo1qlotudgdVaMHxg/P3vH0ShYMEHP/ie7vtsXT/diZaXPbDb88XX8eCD15HPW3D27GjDn8sspdQMjA3MZivA50s1Zb6dkkjYywbGXq/2h2bEwFhKLTDu7q6cybZYgPHxJbz77oDux11c9HF9MRERtZUQWtMpPd2AVUOsZk9TUIGxer75eT98vpTu7FRPTwJCSF0jm86d24/x8SX4/c3psWIUXm8GNlu+2GisEaJRF4QowO3O4ODBFaRSdszP+3XdN5OxYm7Oj7GxFQDacZTRuzdLCZw5cxhHjizprl4ANjPGRn5tlYTDnmK2GADGxlYxOLiOl1460PDnMkvzLQbGBqfNt2teKXU87ty1lNqIgfH6uhO5nHXXUixAK6e+edOv64zg+roTqZS96WfdiYiIduP1pqvKGDf7pG4gkITTmS0GxtV0pAa0E/7d3fFdM8aLix7MzIRw8uRsXdvbCYRo/MimWMwBrzcDiwU4dCgMQP8849nZIKS0bOttY/TA+L33ejA3F8Tp0/qzxcD2UupOpAJjRQgta/zuuwNNGAHWnG7XRsPA2OCaMd9uq0oZ4801xsYLjFdX1boKfYExAExM9O16281yNJZSExFRe1WTMfb5UnC7m3vgqkY23bypZR/n5vxVZegAoK9v98D49ddHAAD33jtT24Z2mEYf60WjruIx3NDQOpzOrO51xmpM5+joSvEyLTA23rGgcubMETgcOTzwgP4GYwDgcmVht+ewvt684+xmWl7eHhgDWmAspcArrzSunFpK1XyLa4ypzYLBZNPXGJfLGLvdGQhRKHYkNJJwWMui71ZKDQAHDqzA4cjpWmfMUU1ERGQUejPGCwvellU6qVnG6+tOxGKuqjLGgPb5ultgfO7cfgwPr5nmJHVzMsZaYGyxSBw4sIJr1/QHxl1dGfT1bR5fGTljnE5b8dJLY7j//qmqM5pCaK+tEzPG2awFa2vuWwLj4eF1jI6u4OWXDzT0ufJ5C0upqf1CoSQiERfy+cYPEi4UgGSyfPMti0Vb+2LEUuqVFRUY754xttkKOHx4WVdgvLDghRCy2DmTiIioXTyejK5xTa2YYawMDGiB7cxMEACqDoz7+uJYXXUjk7GWvD4Wc+Dy5X7TZIsBtWyusRljFRgD2GjAFUIut/ux5NRUN0ZHV4vdqAFjB8avvTaKVMpRVdOtrQIB4762StRxcG/vrQmiBx+cwpUrfVhc9DTkuVIpOwCwlJraLxhMQEpLU/5ok0k7pBQVS698vpRhA2OrdbMT326OHVvE1FQIyaS94u0WF33o7k6UnOtMRETUSl5vetdxTZmMBSsrnpYFxoOD2simt97aB0D/qCalr0/bzuXl0gftFy4Mo1CwmGJ9sRIMJpFIOMueLKhWLObcFhgfPBhGNmvDjRvBivcrFARmZoLb1hcDWmCcTtuRSjVm+xrpzJnD6O+P4vjxxZrub+SgvxL197MzYwxo5dQA8OqrYw15LhUYs5Sa2i4U2hz83miJhPZhq2YlluLzpQ25xjgc9iAUSuqeVXfs2CKktGBysrfi7bRRTSyjJiKi9vN4Mkin7chmy3/YLS15IaVoYWCsBcKvvz4MhyOna0nTVqoiq1w59fnzIwgGEzh4MFzfhnaQRo5sklILjNUaY2CzAddu64wXFrxIp+3FjtSKSkIYLYBcXPTinXcG8fDD723LcFcjEOjMUmo1w7hUxrivL44jR5Ya1p1aJZWYMaa2U4Hx2lrjO1OrdUuVM8Zpw2aMS50lK+fIkSVYrYVdy6m1UU0soyYiovZTJ64rrTPeHNXUqlJq7TNybi6IoaF13SeoFfUZW2pkUyZjwZtv7sPJk7NVP24n2zzWqz8wTqdtyGat2wLj/v4Y3O70ruuMp6e1xlu3Zoy1xzJaYPzCC4cghMTDD1+t+TFUxrjQYYWCy8seCCHLLil88MHrmJ7uxo0b+sZ0VZJK2QCAa4yp/YJBbYdvRsZYfdCWW2MMaGVcRmy+pc0w3n19seJy5TE2tlIxME6lbIhEupgxJiIiQ/B6tc/nSuuMVWDcqs+uQCBZPECudn2xdv8UHI5cyYzx228PIZ22m2p9MbCZMW7EsZ6q8ttaSi0EcPDgyq4Z4+vXu2G15jE8vP33asSMcaEg8MILh3HHHfO6JpSUEwgkUShYdDW5M5Jw2INAIFl26d8DD0xDCIlXXjlQ93OpjDEDY2q7QCAFIWRTRjapUupyXamBzVJqKRv+9DUrFKoPjAGtnPrq1d6yJWnq7DVnGBMRkRGojHGldcYLCz643eliEN1samQTUP36YnX/vr5YycD43LkRuFwZ3HbbQt3b2UlUEqQRx3qqym9rxhjQyqlnZ4PIZMof+k9PhzA8HIHNtj3YMmJgfOnSAMJhD06fvlLX42y+ts4a2RQOe0qWUSvBYBLHjy/gpZcO1H0Mv9l8i2uMqc2sVgm/P4XV1eaVUlfKGPt8aeTzll2bVrVSNOpCPm+tqpQa0ALjbNZa9ozp5qgmllITEVH7qWC3Uq+PxUUfBgZiNa+xrIXKTteSMQZKB8aFgja/+K675k3XANPrzcBmyzc0MN6aMQa0Blz5vKVYLl2K6ki9kxED4zNnjsDjSeN976uvSZt6bZ22zrjUDOOdHnzwOm7e9BdnU9dqs/kWM8ZkAI1u46/oyxhrbxhGWmesZhiHQtVljMfHtY6F5cqpFxa0D2mWUhMRkRHoXWPc6kqnwUHt+YaGag+MFxe92zJZV6/2IhLpMl0ZNaBl0YPBZEOSIOokys6MsWpmVm6d8dqaC5FIFw4cWLnlOocjD5crY5jAOBZz4Ny5/XjooWtwOOo7iRIIdF5grFVO7h4Ynzo1Dau1UPdMY5ZSk6E0evC7Eo87IESh4o6uzjgaKTBWs9uqXVPi82UwPLxWNjBeXPTB603D49n7f/hERGR8Pl/ljHEuZ8HSUutGNSn33TeDU6emMDRUfSk1oAXGyaRjW8B/7twIrNYC7r77RqM2s6M06lhvM2O8fZxlT08Cfn+ybNWcyiSXyhgDWgMuowTGL710ANmstebZxVupwNgor02P9XUXsllrxVJqQHv/uOOOebz88lhd5dTJpNZ8i6XUZAihUGPOIu6USDjg8WQrdn5UZxxjMeO8YaysaC3qqx0RAWjl1JOTfSgUbq0546gmIiIyEpcrC4ulUDZjvLzsgZSWlgfGhw6F8Yu/+AJsttqOttXIpq2dqc+f34/jxxdMe3K6UYFxLOaEEPKWn6NqwFUuY7x7YGyceb8vvHAYo6MrOHCg9LZWw+NJw2IpGOa16aFGNelZUvjgg9cRDnt3HVdaSSplh8ORg8VioIZDTcLAuAP09cUQjboQjzd2nW887qhYRg1sBsZGyhiHw27YbPlbyoT0GB9fRDLpwPT0rUPuOaqJiIiMRAitD0i5jHGrRzU1ivqsVeuM5+d9mJsL4OTJ+taLdrJGZoy1YO/WIObQoTDm5vzF8TtbXb/ejd7eWNkTE0YJjKemgrh2rach2WIAsFi0Y91IpHOaby0vl59hvNO9987Cbs/VVU6dStlNMcMYYGDcEdSg9UoNE2qhZYw7LzBeXdU6Utcy4/D48dLrjHM5geVlDzPGRERkKF5vumzGuFMDY5UxVoHx+fP7AQAnT5pvfbESCiUQjzuRyVjrepxYzFm2Q/nBg2FIaSnZjGl6OlQ83izFKIHxCy8chs2Wx0MPXWvYYwYCSUO8Nr2qyRh3dWVx++0LePvtwZqfL5WymWJ9McDAuCOospZGB8Z6MsYuVxZWa95QgXE47Km68ZbS05NAb2/slsA4HPagUGh9ORoREVElu2WMXa5ssbNup+jqysHnSxUD43PnRjA2toLe3trn0XY6Nct4ba2+AC0WcxYbp+6kGnBdvbq9rDaVsuLmTT/GxsqXJvv9KUSjThTa2DA8l7Pg+98/iJMnZ4vr7xshEEh1VPOt5WUPuroyupcdaCddap/TnEza4XLt/fXFAAPjjhAMphAIJDE11d3Qx00k7LsGxkJszjI2ipUVd13D3I8dW8Tly/3bGhFwVBMRERnRbhnjgYFoS0c1NYrqTB2JuHDlSp+ps8XA1sC4vp4y0aiz7FKzYDCF7u44rl3bfjw5OxuClGLXwLhQsCAeb9/x4OuvDyMWczWsjFppRjb8rbeG8E//dKyhj6mEw7t3pN7K7c4WJ9HUIplkKTUZzOjoahMyxs5dS6kBLTA2Ssa4UABWV7tqaryljI8vYn29Czdv+oqXcVQTEREZ0W4Z40793FKzjF9/fRhSCtx7r3nXFwNao1UAdY/n1Eqpy/dgOXQofEtnalVaPTpauZQaaG/35uefP4JQKI4775xv6OP6/VrGuJ7OzVtNTPTiP//nR/C1r91b7OjcSOGwR9f6YqWrK4NMxoZcrrawL5Wys5SajGV0dBWzs4Gad+pS9GSMAe1sdTRqjBKT9fUu5PNWdHfXlzEGtq8zXlz0wW7PFc/YEhERGUG5jHGhINoyqqlR+vpiWF724OzZUfT2xsp2QzaLzYxx7YGxlFrGuFJgfPBgGAsL/m371NRUNzyedMVqvHYHxisrbrz55hAefvhqw7sjBwIpZLO2kk3JqrWw4MWXv/wI7PY88nkL3n13oAFbuN3ycnUZY5UESyRqa+KbStmYMSZjGRtbRT5vxY0b/oY8XiZjQTZr050xNkopda0zjLfat28dPl9qR2DsRX9/rKaGXkRERM3i8WSQTDqQy22vlw6H3cjnrR0bGPf3x5DPW/Hmm/tw8uRsR5aDN5LXm4bVmq8rME6nrchmbRWndqh1xtevb5ZTT02FMDq6WvF3sDnvtz3Hg888cwIWC3D6dGPLqAGt+RZQf9AfjTrxe7/3g5AS+A//4R9ht+dw6VLtTa9KSSZtiMedVWWM3W4tqK21nFrLGHONMRmIKm+Znm7MOuNEQntj05Mx9vlShimlDoe1wLiejLEQWjn1xMT2jDHXFxMRkdGo7N/Og9pO7UitqM7UUgrTry8GtGOTekc2qSRG5YyxdjypyqnzeYGZmSAOHChfRg20N2M8P+/DP//zUTzyyGRTjtXUa6tnZFMmY8GXv3waKyse/PIvfw/790dw7NgiLl4catRmAqiuI7WijvVrDYy15lvMGJOBDA1F4XDkGrbOWM1E1tPRTssYO1AotP90rsoY17PGGNDKqRcXfVhZ6YKUKmPcmQcXRES0d6nKrp1Njzo9MFYBjtudLi5xMrtQKInV1dqbb8ViWtBaKWPs9WbQ3x8tNuC6edOHbNa2aym715uBEIW2BMbf+MY9sNvz+NjH3mrK49cb9BcKwB/+4Q9gYqIfv/AL38f4+DIA4I47buLGjWBD5lMr9QTG6ti/Gvm8QCbDUmoyGItFYmRkreTsuVqotSUeT/k3T8XrTUNKS01/UI22suKB3Z6v+Kavx9Z1xpGIC+m0vWMPLoiIaO9S2b9Y7NaMcSf3xujujsNqzeOee+ZgszV2zWinqjdjrKr7KmWMAa2cWmWMVSVipY7UgHYc6vOlWx4YX7nSg9deG8MP//A7xXLuRlOPW+vIpr/+6/fh1VfH8BM/cQ733z9dvPzECa1JWCPLqZeXtcC4VaXUat01M8ZkOGNjWmfqRnTNU38c6o+lEhWEqjOR7RQOuxEKJepeizQ2tgqXK4vLl/s5qomIiAxLZYx39vrQOlJ3bm8Mm03il3/5efz4j7/e7k0xjEaVUu+WPDh4MIxw2ItIxImpqRBstjyGhiK7Pn4zxhpVIiXwV391En5/Ek888XbTnkfNfa4lMH7uuaP4+78/gUcfvYwf/uF3tl03OroKrzeFixcbFxiHwx5YrQUEg/pPEqiMcTJZS2CsJcW6urjGmAxmdHQF8bizuM62HpsZY33NtwAYYp3x6qq7qvKRcqxWiSNHljAx0Y/FRY5qIiIiY1LZv52dqdUM4052991zdfUM2WtCoQTicScymdoOz/VmjA8d0hpwXbvWg6mpEEZG1nRl7VsdGL/xxjAuXx7Axz72VlMDM5tNwuutPht+4cIwnn76FO65ZxY/9VNnb0naWCzAiRM3cenSYMNGQS0ve9DdHa+qM3c9pdQqMGbGmAxHlbk0ogHXZsa4swLjcNjdsA/RY8eWMDsbxNWrPRCigL6++gNuIiKiRiqVMS4UtN4YnR4Y03b1jmyKxZwQQu6a9DhwYAVCSFy92oOpqe5dy6gVv791pdSFgsDXv34PBgbW8cgjk01/Pr8/WdVru369G1/96gcwNraKz3zmRVitpQPVEyduYnXVg/n5xkyVqXaGMQC4XDkIUaiplFrNYWZgTIazf/8ahJANWWdcTcbY69XKNdodGBcKAmtrjQyMFyGlwMsvH0BPTwI2W6Ehj0tERNQobncWQshtGeO1NTeyWRsD4z1mMzCurTIwGnXC48mUDdKUrq4choYieP31EUSjLoyNVe5Irfj9qZrX4VbrxRcPYnY2hE984kJL1qAHAindXanX1rrwpS89Aq83jc9+9nsVRxk1ep1xOFzdDGNA63judmdrDIxVKTUDYzIYlyuHgYFoQzpTJxIOOBw5XcHg5hrj9gbGkYgL+byl7o7UyuHDy7Ba84hGXSyjJiIiQ7JYtAzg1s/gTu9ITaXVmzGORp27llErBw+u4Pp1rQHXbh2pFb8/hWTSUXOpt16ZjBXf/ObdOHRoeVszq2aqpkz8zJlDWFtz47Of/d6uze/6++Po7482ZGxTLiewstJVdcYY0CpEVZBbDZZSk6GNja00LGOsJ1sMAE5nHg5HDtFoe5tvNWKG8VYOR744z4+Nt4iIyKg8nvS2jDED470pFNKCrNXV2kup9QbGap0xAIyOrum6jxpr1OzjwWefPYaVFQ9+4ider7vZql7VBMZvvDGMAwfC2L9f38/txImbePvtAeTz9b2YtTU3pLSgp6f642C3O3tLnwI92HyLDG10dBVLS766RyclEg5d64sVny/d9lJqNduvljeEco4fXwDAgwsiIjKuWzPGXlit+YZ+HlL7eb1pWK35utYY688Ya4Fxf39Ud5msGmvUzHXGsZgDzzxzAnfddQO33bbQtOfZKRBIIZHYPRsejToxOdmLe+65ofuxT5yYRyrlKI7IqpUa1dTTU30yx+3OcFyTDgyMO4xqkDAzU1/WuJqMMaC9Wbc7MFZDzRvZwVLNM2ZgTERERuX13pox1kY1cf7vXiJEfSObYjHnrqOalLGxVVgsBd3ri4HNjHEzA+O//dsTSCYdLR/jpTeL2ufYAAAgAElEQVTof/PNfZDSgve9T39gfPvtNyGExKVL9ZVTq+Pg3t5aMsYZJBLVJ9VU+TUDYzIkFRjXW05dfcY41fY1xisrbtjtOd1nQ/W46655fPrT/1LVGxwREVErlVpjzBO6e1M9gXE0qj8wdjjy+Kmfeu2W2buVNDswXl5249lnj+MHfuCq7vLuRtl8bZV/9hcuDCMQSOLAgXDF223l82Vw4MBK3fOMNzPGtawxztY0xziZtMNqLcBuN0eDWgbGHSYQSMLvT9bdgKvajLERSqlXVtzo6Uk0dL2JxSLxwQ9eZUdqIiIyrK0ZYykZGO9loVCyuHSsGum0FZmMrarkwWOPTeLIkWXdt292YPw//sfdAIAf+7E3mvL4lfj92vruSq8tlxN4880h3H33DViqjKBOnJjHlSu9xdLkWiwve+D3J+Fw5Ku+r9udqXmOcVdXtmVrvduNgXGHEULLGk9N1TfLuNqMsVFKqUMhrqciIiJz8Xi09YGFgkAk4kI6bWdgvEcFg0ndY4O2UhUFejPGtXA6c3A4ck0JjGdmgnjxxUN4/PHLNZUK10uVUlcaRzU52YdEwlnV+mLlxImbyOetuHy5v+Zt1EY11fazcbszSKUcVTcAS6VspimjBhgYd6TR0VXcuBFALlfb6ZtCQSuNqDZjnEg4a37ORlhddddUPkJERNTJvN40pBRIJOzsSL3HBYNJxGLOqkciqeRFI5eb7SSE6t7c+ETJX//1PejqyuBHfuRiwx9bD5UNrxQYX7gwDKs1jzvumK/68cfHl2C35+uaZxwOe9DbW9sUFXXMX+3IplTKbqrAuPZ8foewWCxYXdU3n61T9PbOIJc7gcuXBfbt0980QUkknJBSQIiI7p+N1ard7saNZLHcpJUKBYHV1S643St77vdJRERUmfa5NzeXwrVr2lIql+sGVlcj7dwoagKHQyttnp7OoqdnXff9bt70bny13NTjJLc7jnDY1tDnSKdtuHBhBI8/fhbZ7ALadZjndGawtISyr+3cuSEcOXIDqdQSUqnqH//gwTm88UY/nnii+hcopbYGe3z8ak0/eym1Ndvz80n09urfr6JRwGZLmebYe88Hxl1dXXjooYfavRkNNTjowtNPA11d78dDD1UfGN+4oa1TuvPO/XjoIX3rWOLxEL7xDeDo0ffj8OEa3g3qtLBgR6FgwcmT/Xvu90lERFRJoeDHX/wFcPjwKczNBWG1SnzkIydg2/NHcWbkx9e+BoyOPoC779ZfJReNaidMPvCB4zh48EBTtgwARkedWFryNfRYbHJSKx3/wR/sbusxXl9fAU7nGB566Na+M7OzDiwsdONf/+t4zds4MSHw1a/2Ynz8g+jtrW4u8NqaFZmMHffe21vT82cyAfzlXwLj46dw/Lj+BNcf/mEPQqGcaY69WUrdgUZHU3A6C5iYqL45AwBEo1YAgN+v/48yGNRuu7bWnk/hxUUtmB8c1F/+TUREtBf4/VqznfV1G2ZmnBgczDAo3qP6+rSy1aWl6kpe1fFZIFBdwFWtUCiH1dXG7nzT01pp9v79rU+8bNXdncPKSunX9uKLAQDABz5Qe5XG/fdryx/OnvVVfd+bN+s7DvZ6tfeQWMxa1f0SCQs8HvM0qGVg3IFsNuDw4SQmJmpt56/90as/Ej3aHRgvLGgfEP395lnnQEREBGyeyI5EbJiddbY9gKDm6e/XAh8VCOkViWjHZ9UkPWqhgkfZwBHaMzMqMG7e+mg9uruzCIdLn5B48cUAxsZSdW3jsWMJ+P05vPKKv+r7zs9rP6Ohodqe3+fTjvlVDKBXImGF2119F+xOxcC4Qx07lsDEhLumN6b1dZUx7qTAWPuAGBhgxpiIiMwlENA+ryMRK6annW0PIKh5/P48vN4cbtyorsHV2poNPl+u6ZUE3d1Z5HKWqjOPlczMuNDTk217ZrK7u3Q2PJGw4Nw5Hx5+uL7ZylYrcOpUFK++6q/6+H1+vjEZY1U1qlc8boHHw8CYDG58PIlIxFbMpFajllJqVZrTzsDY6SxUFcwTERHtBT6f9hk8M+NCLGbDyAgD471KCGBkJF11YByJ2IpJjGbq7taeo1zJcS1mZpyG2Kd7erJYW7Mht+PH+OqrPmSzlrrKqJX771/HwoKjWD6u182bDrhc+eJJsmqpjHE1JzSkVBljllKTwY2Pa3PMallnXEsptcMh4fHk2xoYDwxkTDNgnIiISLHZAI8nj0uXtM98Zoz3tpGRNGZnq88YtyIwDoW0JW2NXGc8M+PE6Gj7lwd0d+cgpbjlWPeFF4LwePK4557aRiVt9cADWkfoV1+trpx6ft6BoaHaj4NV1reajHEqZUGhIFhKTcZ35EgSQsia1hlHo1ZYLLLqkpVgMNfG5lt2Nt4iIiLTCgZzuHyZgbEZjIykMTfnQL6KeGRtzdb0xlvA1oxx9RWLpSSTFiwtOQyRMd4M+jdfW6GgrS9+6KFIQ8rUh4cz2LcvjVdfra4B18KCo67jYKtVC46ryRjH41qY2O4S91ZiYNyhPJ4C9u9PFz8kqxGNWuHz5as+6xQI5IrNHVptYcFRbEhBRERkNn5/DtmsBUJI7NvX/iCCmmdkJI1czlLsr6JHJGJtUSm1Fjw2qpRaZcZHR9u/T/f0aD+/cHjztV2+7EY4bG9IGTWglcrff/86XnvNV9WJj/n5+gJjQFuSUU3GOJHQbss1xtQRxscTNZZSW4vrlarRroxxLgcsL9sxMMCO1EREZE6qx8bAQAZOZwNbApPhqOxpNeuMtYxx8wMYFXxvzarWwyijmoCtQf/ma3vhhQCEkHjoofWGPc/990cRi9nwzjv6juFTKYHV1forJ73e6jLGiYQWJrKUmjrC+HgSN244EYtV92tcX7cVF+FXo12B8fKyHYWCYMaYiIhMSzXMZBn13jc8rB3v6F1nnEoJpFKtyRjbbFoFYaMyxmpUkxFKqUs1FnvxxQDuvDOOUKhxP9tTp7R5xnrHNqnRXUND9WaM81WNa4rHVcaYpdTUAVQDrsnJ6rLGsZi1owJjjmoiIiKzU+tHjRBAUHP192dgsxV0B8ZqmVsrAmNAW4vbqDXGMzMudHdn4fW2P/jyevOw2wvF17a8bMPbb3saVkathEI5jI8ndDfgalRg7PXmayqlZsaYOsKxY0kAwOXL1TXgWl+vPTBOJKxIp+tvDV2o4v1vcbG+2W1ERESdTpVSM2O891mtwL59Gd2BsUpatKL5FlB+3m8tZmaMM5dbCO21qYzx978fAICGB8aA1p36zTc9SCZ3D8VUYFz/GuNam2+ZJzBuTyclaoje3ixCoWzV64yjUVtVM4wVdSYyErGhv7/8et+XX/bhjTe8WF+3IRq1Fv9t/T6bteDLX76C979/9zUbalZzpeckIiLay1hKbS7VjGxqfcY4h/feczXksWZmnMURRkbQ07OZDX/xxQAGBjI4ejTZ8Od54IF1/PmfD+LCBe+ux8Lz805YLBJ9fa1dY2zGUmoGxh1MCG2d8eRkdRnjaNRa1QxjRb3hrq2VD4y//e1u/MZvHICUAh5PHn5/Dj5fHj5fHmNjqeLXf/d3PXjmmR6dgbEDXV35mrLcREREe4Fa/2iEea/UfCMjabzxhhdSYtcpIipj3KrAuLs7i7Nnqxs3VIoa1WSkkz2hUA7hsA2ZjMArr/jxxBMrNc8OruSee2Kw2ws4cyaw67HwzZsO9PVl6x4XpTLGhQJg0VEzbMZSagbGHW58PIGvf70fuRx0/cGkUgKZjKVYklWNrYFxKWfOBPCbv3kAJ0/G8F/+yyRcrvJdM5NJC/7hH7qRSomKtwPUqKZsU96YiIiIOsGjj67C7c7j8GEGxmYwMpJGPG7dGMNU+ZitHaXUkYhN97FnOSojbqTAuLs7i8nJLpw/70UiYW1KGTUAuFwSH/7wCr75zT58+MMruPvueNnbzs87MDRU/8/I58uhUBBIJCy61nSrrtRdXebJGBtijbEQolsI8awQYnLj/1CZ231HCLEmhPi7Vm+jUR07lkAmY8H16/pKWlQJRa3jmoDSgfHZs1587nOHcOxYAr//+1d2DXYfe2wVqZQV//IvgV2fd2HBwcZbRERkak6nxCOPNOcgnYxneFgLhPSUU6tS6lYFxqGQVjVYb0NW1ZHaSFUQWim1DS+8EITTWcCpU80r8/7sZ2cwOJjBr//6wYoTZhYWHHU33gJQrBbVW04dj1vhdud1ZZf3CqO81M8BeE5KeRTAcxvfl/J7AH6qZVvVAcbHtXUPetcZr69rb2K1Nt8Cbn0jvHTJjX/3745gZCSNr3xlUtdahJMnowgGs/jud0ueA9lmcdHOwJiIiIhMQ3Uf1xMYr63Z4PXm6i611WtzrFF9nanVDGMjdVrv7s4hl7Pg2WdDOHVqfddETz283gK+8IVrWFhw4ItfHC15m3xeK6VuRANadeyvd2STCozNxCiB8ZMAnt74+mkAT5W6kZTyOQDRVm1UJxgdTcHpLGBiQt86Y9WmvZbAWDX+2BoYv/eeC7/4i0cRCuXwB38wuWu5j2KzAR/60BpeeCGAVKp8jXQup80xZmBMREREZlFdxrg1M4yV7m4tY1zvLOPZWadhRjUpm6/N3rQy6q3uvjuOn/3ZeXz72z34znduTRYtL9uRz4uGBMbVZowTCYupGm8BxgmMB6SU8xtf3wQwUM+DCSF+TghxVghxNhLZ22VHNhtw+HBSd8ZYBca1dKW22bT7qcB4dtaBz3zmKOz2Av7gDybQ11dd1+jHHltFMmnFSy+VL6deXrZDSoGBAXakJiIiInNwubQuxDdu6MsYtzIwDoW051pdrTdj7DJUthjYzIYDzRnTVMqnPjWPu++O4Xd+Zww3bji2XdeoUU3A1oyx/lJqM41qAloYGAshviuEuFji35NbbyellADqqluQUv6RlPI+KeV9gcDua1g73fh4ApcvuyF1/NRU+UStHZ6DQS0wXlqy4zOfGUcmY8FXvzqJkZHq/2DvvTeKQCBXsZxavSH09zNjTEREROYxMpLWHRgHAq0LYDZLqetfY2yk9cXAZsb46NEEBgdbk5Sx2YAvfOEaAODXf/0gclvOcczPa8fBjVhjXG1gnEhYWErdLFLKx6SUd5T49zcAFoQQQwCw8f9iq7ZrLxgfTyISsWFxcfczd+vrtZdSA1pgPDPjxGc+cxSrqzZ85SuTOHKktjc1rZx6tWI59cKC9obAUmoiIiIyk+FhfbOMI5HWZoy93jxstgJWV2sPjNWoJqNljHt7tWC4VdliZd++DD73uWm8+aYXf/InQ8XLG5sx1vYR/YGxFW43S6nb4RkAn9z4+pMA/qaN29JxxscTAPQ14KpnjTGgdTx85x0PZmed+NKX3sMddyRqehzlscdWkUhY8fLL/pLXLy427g2BiIiIqFOMjKSxuOio2IsFUBnj1gXGQmhZ43C49lJqFfCPjhorMA4G8/jKVybxMz9zs+XP/cQTK3jiiTD++I+H8MYbHgBaYBwI5BoSoNbSlZql1O3xuwAeF0JMAnhs43sIIe4TQvyxupEQ4gUA3wDwqBBiVgjxQ23ZWoM5elTrTH358u4NuKJRG1yuPOz22qrVe3uzsFolfvu3r+LUqfr7oN13n1ZO/dxzpcupFxbscLvzplv8T0REROamsqlzc+Wzxum0QDLZ2uZbgLbOuJ6MsRFHNSkPPbTetuPOX/u16W0jnBrVkRrQKjVdrnwVgbHFdIFxixq7VyalDAN4tMTlZwH8my3fP9zK7eoUHk8B+/encOmSZ9fbRqNW+P217+Q///Nz+NjHlnH77fVlihWbDXjkkTV897shpNMCTuf2gF3NMBaVT5YSERER7SlbRzYdOlQ6gFQzjFsdGGvzfmvPGBtxVJMRqBFOP/dzx/DFL45ift7Z0J+Rz5fXPa6JpdTUsT74wQheesm/ayOEaNRaLKWoRW9vrmFBsfLYY6uIx0uXUy8sONDfz47UREREZC56ZhmrSSGtLKUG6s8YG3FUk1FsHeF09aoLQ0ONDox3zxjnckAmw+Zb1KGefHIZuZwF//AP3RVvt75uq2lUUzOdOrVetju1yhgTERERmUkgkIfHk6/YmbpdGePubi1jrGciSilGHNVkJJ/61DzuuisGKRszw1jxevWVUsfj2m3MtpSRgfEecehQCnfdFcO3vtVb8U0qGrXW3HirWWw24PTpNZw5E0Qms1kznc0KrKzYGBgTERGR6Qixe2fqdmaM02kLksnaQonZWeONajISNcLpttviOHky1rDHrTYwZsaYOtZTTy3j+vWuYie7UowYGAOly6mXluyQUjAwJiIiIlMaGakcGEciWgDTjowxUNss41RKYHHReKOajGZ4OIM///N3G7qEUW8pdSKhhYhma77FwHgPefzxVXg8eXzrW71lb2PUwPj++9fh928vp1ZzmQcGuMaYiIiIzGdkJI25OQfyZQ7dVMa4HV2pAWB1tfoGXEYd1WQGPl9OV2DMUmrqeF1dBfzQD63g2We7EYvd+qvN54FYzHhrjIGt5dSBYjm1Gmre38+MMREREZnPyEga2awFS0ulA9C1NRs8njxsLZ4z092tHUvWkjGennYBAPbvZ2Dcaqor9W5rwxMJllLTHvDUU8tIpy34zndubcKlzv7U05W6mR59dBWxmA2vvuoDoDXeAsBSaiIiIjKl3TpTRyK2lmeLASAU0qr5aulMrWYY79/PNcat5vHkkc8LpNOV56DG4yylpj3gttsSGB9P4G/+5tZy6vV1LTCuZ45xMz3wQBQ+32Y59eKiAx5Pnq38iYiIyJR2C4zX1mwtb7wFbJZSh8PVl1LPzDgRCnFUUzuo5ZS7zTLezBib63fEwHiPEUIb3fTOOx68+27XtutUFzqfz3il1ABgt0ucPr2G558PIpsVWFiwM1tMREREptXfn4HVKsuObFpba0/G2OmU8HjyNWaMXSyjbpPNwLjyOmN2paY944knVuBwFG7JGq+va29eRmy+pTz22CqiURteecWHxUXOMCYiIiLzstmAffvKd6ZuVyk1APT0aLOMqzUz42Rg3Cb6A2NVSs2MMXU4vz+PRx9dxbe/3Y1UanMNgfojMGopNaCVU3u9OTz3XAgLCw7097MjNREREZlXpZFN7SqlBrRy6mozxmpUE9cXt4fqM7TbLONEwgqHowC7fZcuXXsMA+M96sknlxGL2fDcc5vjj1RgbNRSakCVU0fwz/8cRDjMUmoiIiIyt3KBcSYjkEhY25Yx7u6uPmOsXgczxu2hYoDdMsaJhMV0ZdQAA+M96957Y9i/P7WtnFottDdyKTWglVPHYtq2MjAmIiIiMxseTiMatRWbqCqRiHas1EkZYzWqiTOM20Nvxjget5qujBpgYLxnqSZc58/7MDWlnZ1bX7fCapWG7zD3wAPrxfbwDIyJiIjIzMp1pl5b04LSdmaM19ZsyFeRb+GopvbS25U6HrcyY0x7y0c/GobVKotZ42jUCq83D1F5dFnbORxad2oAGBjgGmMiIiIyr3KBcSSiZf3aFRiHQjkUCqLY3FUPjmpqL6dTwuEo6FhjbDHdDGOAgfGe1tubw8MPr+Hv/q4H2axANGoz9PrirX7yJxfw6KOrxQ8DIiIiIjMaHtaq54yXMdaed2WlmsCYo5razevN61hjbDV8hWkzMDDe4556ahkrK3a88EIA0ajV0B2ptzp+PIkvfvGq6brhEREREW3V1VVAT0/WcIFxKKRV9VWzzpijmtpPT2CsrTHujJihkRgY73EPPriO/v4MvvWt3mIpNRERERF1jlKdqVVgHAi059huM2OsrzM1RzUZg8+X11VKzYwx7Tk2G/AjPxLGSy/5MT3tgt/fGaXURERERKQZGUnjxo2da4xt8Hjybauu6+7WMsZ6S6k5qskYfL6crowxm2/RnvSjP7oMKQUiEZvhRzURERER0XYjI2ksLtqRyWx2UF1bs7WtjBoA/P48rFapO2M8M6ONamJg3F5eb+WMcaGgrTFmKTXtScPDGTzwwDoA488wJiIiIqLthofTkFJgbs5RvCwSsbVthjEAWCza+ma9a4ynp5kxNgKfL19xXFMyqYWHnGNMe9ZTTy0DYGBMRERE1GlKjWxqd8YY0Mqp9WaMZ2edCAazPBZts90yxomEdh1LqWnPOn16DU88Ecb73x9p96YQERERURVKBcbtzhgD2ixj/RljF0ZHmS1uN58vj3Tasq0sf6t4XGWMGRjTHuVwSHzhC9dx/Hiy3ZtCRERERFUIhXJwu/PbGnAZJ2Osv/mWCvCpfVTGvlzWOB5XGWOWUhMRERERkYEIsX1kUzYrEI9bDZIx3r2UOpUSWFhwYHSUo5raTY1uLdeZmqXURERERERkWMPDm4FxJKIFL+3OGPf2ZhGPW3Hliqvi7dR2M2Pcfj6fts+UC4xVKbUKoM2EgTERERERkcGpWcaFglZGDbQ/MP7IR8Lo7c3gs589UgzWS1GjmrjGuP1UwFuulHozY8xSaiIiIiIiMpjh4TQyGQuWluzFwDgQaG9Wr7c3h9/7vatYXLTj858/hFyZOJ2jmoxjtzXGiYQWHrKUmoiIiIiIDGdrZ2qjZIwB4M474/j856fx6qt+fOUrIyVvw1FNxrG5xrh00zTVfMuMc4z1tZEjIiIiIqK2UYHxjRtOZLPaqB0jBMYA8KM/GsbkZBe+9rUBjI8n8NGPrmy7fnraxWyxQaiTE+XXGFthsUi4XOYLjJkxJiIiIiIyuMHBDKxWuS1j3O6u1Fv90i/N4tSpdfz2b4/h4kX3tutmZ50MjA2iq6sAq1VW6Eptgdudhyg95nhPY2BMRERERGRwNpsWHKvA2O3Ow+GQ7d6sIpsN+J3fuYq+vix+5VcOY2lJG+PEUU3GIoRWTl1pjrEZy6gBBsZERERERB1BzTKORGyGyhYrwWAeX/rSFcTjVvzqrx5COi04qsmAfL5cxa7UZmy8BTAwJiIiIiLqCGpk09qazTDri3c6ciSF3/zN67h40Yvf/d1RjmoyIK83v0sptTkzxmy+RURERETUAUZG0ohEbJiddWJ42LiB5qOPruHTn57Df/tv+/Duu9p6Y64xNg6fL1+xK7XHw4wxEREREREZlCpHnp52GbKUeqtPf3oep0+vYXLSzVFNBlMpYxyPs5SaiIiIiIgMbOs6XaOWUisWC/Bbv3UNhw8nMT6ebPfm0BY+X744r3inRMJi2uZbLKUmIiIiIuoA+/Z1TmAMAB5PAU8//Q6kNOHsHwOrvMaYGWMiIiIiIjIwj6eA7u4sACAQ6IzgxeWS6OoyZwbSqHy+PBIJK3I7zq1ICcTjFq4xJiIiIiIiY1Pl1J2QMSZj8vm0fWfnyKZMRiCXM29XagbGREREREQdQnWjNnrzLTIur1fLCO8MjBMJ7XuWUhMRERERkaExY0z1KhcYx+OWbdebzZ5vvmW1WrG0tNTuzSAiIiIiqtuBAwV4PH2w2+ewtMTgmKqXz+cAHMHMTAw9PSvFy2/c8AEAcrk1U8ZPQkrZ7m1oqvvuu0+ePXu23ZtBRERERNQQUgKCjZ6pRm+8AdxzD/DNbwIf//jm5S++CDz8MPBP/wQ8/nj7tq+ZhBDnpJT3lbqOpdRERERERB2EQTHVIxjU/l9b2375+rr2v8/X2u0xCgbGREREREREJqEC40hk++XRqPY/A2MiIiIiIiLa03w+repgZ8ZYBcZ+f+u3yQgYGBMREREREZmExaIFv+UCY2aMiYiIiIiIaM8LBssHxl5v67fHCBgYExERERERmUgwWHqNcVcXYNvzA31LY2BMRERERERkIoFA6a7UZi2jBhgYExERERERmUq5UmqzNt4CGBgTERERERGZSrnAmBljIiIiIiIiMoVya4wZGBMREREREZEpqMC4UNi8jIExERERERERmUYgAEi5OaIJYPMtBsZEREREREQmEgxq/29dZ8yMMREREREREZmGCoy3rjNmV2oiIiIiIiIyjZ0Z43weSCSYMSYiIiIiIiKTCAS0/1VgHItp/zMwJiIiIiIiIlPYmTFeX9f+Z2BMREREREREprAzMFbdqRkYExERERERkSmoUmrVfEsFxmy+RURERERERKZgswFeLzPGWzEwJiIiIiIiMplAgIHxVgyMiYiIiIiITCYYZPOtrRgYExERERERmUwweOsaYwbGREREREREZBpbM8ZsvsXAmIiIiIiIyHR2rjG22QCns73b1E4MjImIiIiIiExmZ8bY5wOEaO82tRMDYyIiIiIiIpNRa4yl3AyMzYyBMRERERERkckEg0AuByQSWldqBsZERERERERkKsGg9v/aGjPGAANjIiIiIiIi0wkEtP9VYGzmjtQAA2MiIiIiIiLTYcZ4OwbGREREREREJqMC40iEgTHAwJiIiIiIiMh0tmaM2XyLgTEREREREZHpqDXGq6vMGAMGCYyFEN1CiGeFEJMb/4dK3OYeIcRLQohLQog3hRA/3o5tJSIiIiIi6nQqML55EygU2HzLEIExgM8BeE5KeRTAcxvf75QA8NNSyhMAPgzgy0KIYAu3kYiIiIiIaE9wubR/MzPa98wYG8OTAJ7e+PppAE/tvIGUckJKObnx9RyARQB9LdtCIiIiIiKiPSQYZGCsGCUwHpBSzm98fRPAQKUbCyHuB+AA8F6Z639OCHFWCHF2aWmpsVtKRERERES0BwQCwPS09rXZA2Nbq55ICPFdAIMlrvr3W7+RUkohhKzwOEMA/hzAJ6WUhVK3kVL+EYA/AoD77ruv7GMRERERERGZVTAIvPGG9jUD4xaRUj5W7johxIIQYkhKOb8R+C6WuZ0fwN8D+PdSypebtKlERERERER7XjAIpFLa12y+ZQzPAPjkxtefBPA3O28ghHAA+J8A/kxK+d9buG1ERERERER7TnBLK2OzZ4yNEhj/LoDHhRCTAB7b+B5CiPuEEH+8cZv/DcAHAfyMEOLCxr972shrRxIAAAfsSURBVLO5REREREREnY2B8aaWlVJXIqUMA3i0xOVnAfybja//AsBftHjTiIiIiIiI9iQ1yxhgYGyUjDERERERERG10NaMsdfbvu0wAgbGREREREREJqQCY48HsJg8MjT5yyciIiIiIjInFRibvSM1wMCYiIiIiIjIlNQaY7OvLwYYGBMREREREZmSyhgzMGZgTEREREREZEoMjDcxMCYiIiIiIjIhBsabGBgTERERERGZEJtvbWJgTEREREREZEJdXYDNxowxANjavQFERERERETUekIAn/408MQT7d6S9mNgTEREREREZFL/9b+2ewuMgaXUREREREREZGoMjImIiIiIiMjUGBgTERERERGRqTEwJiIiIiIiIlNjYExERERERESmxsCYiIiIiIiITI2BMREREREREZkaA2MiIiIiIiIyNQbGREREREREZGoMjImIiIiIiMjUGBgTERERERGRqTEwJiIiIiIiIlNjYExERERERESmxsCYiIiIiIiITI2BMREREREREZkaA2MiIiIiIiIyNQbGREREREREZGoMjImIiIiIiMjUGBgTERERERGRqTEwJiIiIiIiIlNjYExERERERESmxsCYiIiIiIiITI2BMREREREREZmakFK2exuaSgixBGCq3dtBHa8XwHK7N4KoBtx3qVNx36VOxP2WOpVZ9t0xKWVfqSv2fGBM1AhCiLNSyvvavR1E1eK+S52K+y51Iu631Km477KUmoiIiIiIiEyOgTERERERERGZGgNjIn3+qN0bQFQj7rvUqbjvUififkudyvT7LtcYExERERERkakxY0xERERERESmxsCYiIiIiIiITI2BMZmWEOJPhBCLQoiLWy67WwjxkhDiLSHE3woh/DvuMyqEiAkhfmXLZR8WQlwWQlwRQnyula+BzKfa/VYIcdfGdZc2rndtXH7vxvdXhBBfEUKIdrweMo9q9l0hhF0I8fTG5e8IIT6/5T58z6WWEULsF0L8sxDi7Y330V/auLxbCPGsEGJy4//QxuVi4z31ihDiTSHEyS2P9cmN208KIT7ZrtdE5lDDvvt/bOyzbwkh/kUIcfeWxzLF+y4DYzKzPwXw4R2X/TGAz0kp7wTwPwH86o7rfx/At9U3QggrgD8A8ASA2wH870KI25u1wUSoYr8VQtgA/AWAX5BSngDwCIDsxn3+XwCfBnB049/OxyRqtD+F/vfcTwBwblx+L4CfF0Ic4HsutUEOwGellLcDeBDAZzb2uc8BeE5KeRTAcxvfA9q+qd5Xfw7aey2EEN0A/iOABwDcD+A/qoCEqEmq3XevATi98b77BWw04zLT+y4DYzItKeUZACs7Lh4HcGbj62cB/Ji6QgjxFLQ3jUtbbn8/gCtSyqtSygyAvwLwZNM2mkyvyv32XwF4U0r5xsZ9w1LKvBBiCIBfSvmy1Dow/hmAp5q/9WRmVe67EoBn4+ROF4AMgHXwPZdaTEo5L6U8v/F1FMA7AIah7XdPb9zsaWy+hz4J4M+k5mUAwY333B8C8KyUckVKuQptf+cJSWqaavddKeW/bOybAPAygJGNr03zvsvAmGi7S9j8Y/8EgP0AIITwAvg1AP/3jtsPA5jZ8v3sxmVErVRyv4UWdEghxD8KIc4LIf6vjcuHoe2rCvdbapdy++5/BxAHMA9gGsB/klKugO+51EZCiAMA3gfgFQADUsr5jatuAhjY+LrcPsp9l9pG57671c9is0LSNPsuA2Oi7T6F/7+9OwiVuoriOP79lQWVQWEERYgGtatFiAoZUYGQrQKRKDSinbUIWggiEQYRLaxFRZt6qwiCHvSgR+5CcCVCFJZEm8JHJJUoEUHqcXFvOgvfwBBv5uH/+9kM3PufP3dxODNn7v2fgb1JjgO30nYpAF4H3qmqv2a1MGmM5eJ2DbANeK6/Pp3kidksUbqq5WJ3M3ABuBvYCLya5N7ZLFG6/AP558ArVXVudK6fvPH/T7UqTRq7SR6jFcb7prbIVWLNrBcgrSZVdZJ2/JQk9wNP9aktwM4kbwO3AReT/AMc58oOB7RjJ0vTW7E0Nm5PAUeq6vc+twg8RHvu+J6RWxi3mokxsfss8FVV/QucTnIU2ETbtTDnaqqS3EArLD6pqvk+/FuSu6rq135U+nQfX+LqMbpE6/MwOv71Sq5bmjB2SfIgrffDk1X1Rx9eLqavOe4YSyOS3NlfrwMOAB8CVNUjVbWhqjYA7wJvVtV7wDHgviQbk9wIPAMszGTxGqzl4hY4DDyQ5Ob+rOajwPf9CNW5JFt7N+o9wBczWLoGbkzs/gI83uduoTWOOYk5V1PWc+RHwA9VdWhkagH4r7P081zJoQvAnt6deitwtufcw8D2JLf3plvb+5i0IiaN3STrgXlgd1X9OHL9YPKuO8YarCSf0n69vSPJKVq3yLVJXuqXzANz4+5RVeeTvEz7cLse+LiqTox7j/R/TBK3VXUmySHah1oBi1X1Zb9uL61L8E2054gud1uXVsKEOfd9YC7JCSDAXFV92+9jztU0PQzsBr5L8k0f2w+8BXyW5EXgZ2BXn1sEdgA/AX8DLwBU1Z9J3qDlY4CD/bl5aaVMGruvAeuAD1pNzfmq2jSk77ppR8slSZIkSRomj1JLkiRJkgbNwliSJEmSNGgWxpIkSZKkQbMwliRJkiQNmoWxJEmSJGnQLIwlSZIkSYNmYSxJkiRJGrRLMuapWYDyVxQAAAAASUVORK5CYII=\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "ncfAnPi_xBNt"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}